Method and System for Providing Dynamic Orthodontic Assessment and Treatment Profiles

ABSTRACT

Method and system for displaying an orthodontic related image including one or more image segments, selecting one or more movement indicators associated with a corresponding one or more of the image segments, and dynamically displaying a modified orthodontic related image based on the selected one or more movement indicators are provided.

RELATED APPLICATIONS

The present application claims priority under 35 USC § 120 to pendingapplication Ser. No. 11/581,224 entitled “Method and System forProviding Dynamic Orthodontic Assessment and Treatment Profiles” filedOct. 13, 2006 which claims priority to application Ser. No. 10/788,635entitled “Dental Data Mining” filed on Feb. 27, 2004, and to applicationSer. No. 11/379,198 entitled “Method and System for Providing Indexingand Cataloguing of Orthodontic Related Treatment Profiles and Options”filed Apr. 18, 2006, the disclosure of each of which are incorporatedherein by reference for all purposes.

FIELD OF THE INVENTION

The present invention is related generally to the field of orthodontics.More specifically, the present invention is related to methods andsystem for providing dynamic orthodontic assessment and treatmentprofiles.

BACKGROUND

A primary objective of orthodontics is to realign patients' teeth topositions where the teeth function optimally and have an aestheticappearance. The goal of a doctor is to take the patient from theircurrent condition (“initial” or “starting dentition”) to a finalcondition (“treatment goal”). The result achieved is known as the“treatment outcome.” There may be many ways to achieve the goal andthese are known as “treatment options.” The methodologies used by thedoctor to get the patient to the goal are the known as the “treatmentplan.”

Often times, doctors establish the goal as “ideal” and discontinuetreatment when they are as close as they can possibly get to the ideal.However, more recently with the growing use of 3-D computer graphicssoftware services and programs in dentistry, the doctor can actuallyestablish a custom treatment goal specific to each individual patient,and this goal may be a limited treatment goal and not ideal in everycomponent of the bite. This is important because if the doctor is ableto achieve 100% of the intended limited goal, the treatment may still bedeemed a success, whereas it may be possible that if the doctor onlyachieves 75% of a completely “ideal” treatment goal, the treatment mightnot be deemed a success even though the amount of measured improvementon an absolute scale in the latter situation might be higher than in thelimited treatment situation.

Typically, appliances such as fixed braces and wires are applied to apatient's teeth to gradually reposition them from an initial arrangementto a final arrangement. The diagnosis and treatment planning process oforthodontic cases can be imprecise as the final dentition of a patientis based on the knowledge and expertise of the treating doctor inassembling various parameters in an assessment of each patient'scondition and in a determination of a final position for each tooth.Different clinicians will vary in their definitions of individualorthodontic parameters and their definition of how a case should ideallybe treated will also often vary.

To overcome some of these subjective issues, various indices have beenused to more objectively define a patient's initial dentition and finaloutcome. For example, the PAR (Peer Assessment Rating) index identifieshow far a tooth is from a good occlusion. A score is assigned to variousocclusal traits which make up a malocclusion. The individual scores aresummed to obtain an overall total, representing the degree a casedeviates from ideal functional alignment and occlusion. The PAR graderis then calibrated to a known standard set of orthodontic conditions sothis individual is able to rate new cases similarly.

In PAR, a score of zero would indicate ideal alignment and positioningof all orthodontic dental components as defined by generally acceptedocclusal and aesthetic relationships the orthodontic community hasadopted, and higher scores would indicate increased levels ofirregularity. The overall score can be recorded on both pre- andpost-treatment dental casts. The difference between these scoresrepresents the degree of improvement as a result of orthodonticintervention. In addition to the PAR index, other indices may be usedsuch as ICON, IOTN and ABO. These indices also rely on individual dentalmeasurements in order to derive an assessment of deviation from anideal.

In view of the foregoing, it would be desirable to have methods andsystems to provide dynamic orthodontic related assessment, diagnosisand/or treatment profiles.

SUMMARY OF THE INVENTION

Method and system for projecting a first orthodontic related image at apredetermined location within a display unit, selecting a secondorthodontic related image on the display unit, and projecting the secondorthodontic related image at the predetermined area within the displayunit such that a difference between the first orthodontic related imageand the second orthodontic related image is displayed at thepredetermined area within the display unit are provided.

These and other features and advantages of the present invention will beunderstood upon consideration of the following detailed description ofthe invention and the accompanying drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1A shows one exemplary dental data mining system;

FIG. 1B shows an analysis of the performance of one or more dentalappliances;

FIG. 1C shows various Movement Type data used in one embodiment of thedata mining system;

FIG. 1D shows an analysis of the performance of one or more dentalappliances;

FIGS. 1E-1F show various embodiments of a clusterizer to generatetreatment plans;

FIG. 2A is a flowchart of a process of specifying a course of treatmentincluding a subprocess for calculating aligner shapes in accordance withthe invention;

FIG. 2B is a flowchart of a process for calculating aligner shapes;

FIG. 3 is a flowchart of a subprocess for creating finite elementmodels;

FIG. 4 is a flowchart of a subprocess for computing aligner changes;

FIG. 5A is a flowchart of a subprocess for calculating changes inaligner shape;

FIG. 5B is a flowchart of a subprocess for calculating changes inaligner shape;

FIG. 5C is a flowchart of a subprocess for calculating changes inaligner shape;

FIG. 5D is a schematic illustrating the operation of the subprocess ofFIG. 5B;

FIG. 6 is a flowchart of a process for computing shapes for sets ofaligners;

FIG. 7 is an exemplary diagram of a statistical root model;

FIG. 8 shows exemplary diagrams of root modeling;

FIG. 9 show exemplary diagrams of CT scan of teeth;

FIG. 10 shows an exemplary user interface showing teeth;

FIG. 11 is a block diagram of the overall system for practicing thevarious embodiments of the present invention;

FIG. 12 illustrates a tabular representation of the indexing systemstored in the storage unit of FIG. 11 in accordance with one embodimentof the present invention;

FIG. 13 illustrates a representation of possible treatment goals for anygiven orthodontic case in one aspect of the present invention;

FIG. 14 illustrates a matrix representation for the possible treatmentgoals shown in FIG. 13 formatted in accordance with the tabularrepresentation shown in FIG. 12 in accordance with one embodiment of thepresent invention;

FIG. 15 illustrates the lower arch length category for use in theindexing system in accordance with one embodiment of the presentinvention;

FIG. 16 illustrates the selection process display for use in theindexing system for the identified primary concern as “buck teeth” inaccordance with one embodiment of the present invention;

FIG. 17 illustrates an exemplary selection process display 1700 forcapturing one component of the sagittal dimension discrepancy for thepatient's right side in one embodiment of the present invention;

FIG. 18 illustrates an exemplary selection process display 1700 forcapturing one component of the sagittal dimension discrepancy for thepatient's left side in one embodiment of the present invention;

FIG. 19 illustrates an exemplary selection process display 1900 forcapturing one component of the vertical dimension in one embodiment ofthe present invention;

FIG. 20 illustrates an exemplary selection process display 2000 forcapturing one component of the horizontal/transverse dimension in oneembodiment of the present invention;

FIG. 21, an exemplary selection process display 2100 for capturing onecomponent of the arch length discrepancy category in accordance with oneembodiment of the present invention;

FIG. 22 illustrates an exemplary selection process display 2200 forcapturing another component of the arch length discrepancy category inaccordance with one embodiment of the present invention;

FIG. 23 illustrates an exemplary patient summary display 2300 displayedon terminal 1101 for use in the indexing system in accordance with oneembodiment of the present invention;

FIG. 24 illustrates a patient database 2400 in accordance with oneembodiment of the present invention;

FIG. 25 illustrates the selection process for representative componentsfor use in the indexing system in accordance with an embodiment of thepresent invention;

FIG. 26 illustrates an exemplary series of database addresses generatedby combining the initial condition address with the treatment goaladdress in one embodiment of the present invention;

FIG. 27 illustrates an exemplary database for a patient in anotherembodiment of the present invention;

FIG. 28 is a flowchart illustrating the procedure for identifying adentition profile using the indexing system in accordance with oneembodiment of the present invention;

FIG. 29 is an example user interface display for initiating sampleorthodontic case assessment in accordance with one embodiment of thepresent invention;

FIG. 30 is an example user interface display for providing patientdesired orthodontic treatment information in accordance with oneembodiment of the present invention;

FIGS. 31-34 are an example user interface displays for providing patientorthodontic condition information in accordance with one embodiment ofthe present invention;

FIGS. 35A-35C are example user interface displays illustrating imageselection and associated enlarged display at a predetermined area of thedisplay in accordance with one embodiment of the present invention;

FIG. 36 is an example user interface display providing treatment goalsassociated with the patient orthodontic condition information andpatient desired orthodontic treatment information in accordance with oneembodiment of the present invention;

FIG. 37 is an example user interface display providing a similar sampletreatment case corresponding to the selected treatment goal for thepatient orthodontic condition information in accordance with oneembodiment of the present invention;

FIGS. 38A-38B illustrate a manual visual aid for patient orthodonticcondition assessment and related treatment difficulty level inaccordance with one embodiment of the present invention;

FIG. 39 is an example user interface display for illustrating treatmentplan information in accordance with one embodiment of the presentinvention;

FIG. 40 is an example user interface display for modifying a treatmentplan parameter in accordance with one embodiment of the presentinvention;

FIG. 41 illustrates example treatment difficulty categories fororthodontic treatment plans in accordance with one embodiment of thepresent invention;

FIG. 42 is a block diagram illustrating an orthodontic self-assessmentsystem in accordance with one embodiment of the present invention;

FIG. 43 illustrates an example user interface for receiving user dentalcondition information in the system of FIG. 42;

FIG. 44 is a flowchart illustrating an orthodontic self-assessmentprocedure in accordance with one embodiment of the present invention;

FIG. 45 is a flowchart illustrating an orthodontic self-assessmentprocedure in accordance with another embodiment of the presentinvention;

FIG. 46 is a flowchart illustrating image selection process for patientorthodontic condition determination in accordance with one embodiment ofthe present invention;

FIG. 47 is a flowchart illustrating the treatment plan parametermodification in accordance with one embodiment of the present invention;

FIG. 48 is an example user interface for providing real time dynamicrepresentation of orthodontic conditions in accordance with oneembodiment of the present invention;

FIG. 49 is an example user interface for providing dynamic orthodonticcondition validation in accordance with one embodiment of the presentinvention;

FIG. 50 is a flowchart illustrating real time dynamic orthodonticcondition representation in accordance with one embodiment of thepresent invention; and

FIG. 51 is a flowchart illustrating dynamic orthodontic conditionvalidation in accordance with one embodiment of the present invention.

DETAILED DESCRIPTION

Digital treatment plans are now possible with 3-dimensional orthodontictreatment planning tools such as ClinCheck® software from AlignTechnology, Inc. or other software available from eModels and OrthoCAD,among others. These technologies allow the clinician to use the actualpatient's dentition as a starting point for customizing the treatmentplan. The ClinCheck® technology uses a patient-specific digital model toplot a treatment plan, and then use a scan of the achieved treatmentoutcome to assess the degree of success of the outcome as compared tothe original digital treatment plan as discussed in U.S. patentapplication Ser. No. 10/640,439, filed Aug. 21, 2003 and U.S. patentapplication Ser. No. 10/225,889 filed Aug. 22, 2002. The problem withthe digital treatment plan and outcome assessment is the abundance ofdata and the lack of standards and efficient methodology by which toassess “treatment success” at an individual patient level. To analyzethe information, a dental data mining system is used.

FIG. 1A shows one exemplary dental data mining system. In this system,dental treatment and outcome data sets 1 are stored in a database orinformation warehouse 2. The data is extracted by data mining software 3that generates results 4. The data mining software can interrogate theinformation captured and/or updated in the database 2 and can generatean output data stream correlating a patient tooth problem with a dentalappliance solution. Note that the output of the data mining software canbe most advantageously, self-reflexively, fed as a subsequent input toat least the database and the data mining correlation algorithm.

The result of the data mining system of FIG. 1A is used for definingappliance configurations or changes to appliance configurations forincrementally moving teeth. The tooth movements will be those normallyassociated with orthodontic treatment, including translation in allthree orthogonal directions, rotation of the tooth centerline in the twoorthogonal directions with rotational axes perpendicular to a verticalcenterline (“root angulation” and “torque”), as well as rotation of thetooth centerline in the orthodontic direction with an axis parallel tothe vertical centerline (“pure rotation”).

In one embodiment, the data mining system captures the 3-D treatmentplanned movement, the start position and the final achieved dentalposition. The system compares the outcome to the plan, and the outcomecan be achieved using any treatment methodology including removableappliances as well as fixed appliances such as orthodontic brackets andwires, or even other dental treatment such as comparing achieved to planfor orthognathic surgery, periodontics, restorative, among others.

In one embodiment, a teeth superimposition tool is used to matchtreatment files of each arch scan. The refinement scan is superimposedover the initial one to arrive at a match based upon tooth anatomy andtooth coordinate system. After teeth in the two arches are matched, thesuperimposition tool asks for a reference in order to relate the upperarch to the lower arch. When the option “statistical filtering” isselected, the superimposition tool measures the amount of movement foreach tooth by first eliminating as reference the ones that move(determined by the difference in position between the current stage andthe previous one) more than one standard deviation either above or belowthe mean of movement of all teeth. The remaining teeth are then selectedas reference to measure movement of each tooth.

FIG. 1B shows an analysis of the performance of one or more dentalappliances. “Achieved” movement is plotted against “Goal” movement inscatter graphs, and trend lines are generated. Scatter graphs are shownto demonstrate where all “scattered” data points are, and trend linesare generated to show the performance of the dental appliances. In oneembodiment, trend lines are selected to be linear (they can becurvilinear); thus trend lines present as the “best fit” straight linesfor all “scattered” data. The performance of the Aligners is representedas the slope of a trend line. The Y axis intercept models the incidentalmovement that occurs when wearing the Aligners. Predictability ismeasured by R² that is obtained from a regression computation of“Achieved” and “Goal” data.

FIG. 1C shows various Movement Type data used in one embodiment of thedata mining system. Exemplary data sets cover Expansion/Constriction(+/−X Translation), Mesialization/Distalization (+/−Y Translation),Intrusion (−Z Translation), Extrusion (+Z Translation), Tip/Angulation(X Rotation), Torque/Inclination (Y Rotation), and Pure Rotation (ZRotation).

FIG. 1D shows an analysis of the performance of one or more dentalappliances. For the type of motion illustrated by FIG. 1D, the motionachieved is about 85% of targeted motion for that particular set ofdata.

As illustrated saliently in FIG. 1D, actual tooth movement generallylags targeted tooth movement at many stages. In the case of treatmentwith sequences of polymer appliances, such lags play an important rolein treatment design, because both tooth movement and such negativeoutcomes as patient discomfort vary positively with the extent of thediscrepancies.

In one embodiment, clinical parameters in steps such as 170 (FIG. 2A)and 232 (FIG. 2B) are made more precise by allowing for the statisticaldeviation of targeted from actual tooth position. For example, asubsequent movement target might be reduced because of a largecalculated probability of currently targeted tooth movement not havingbeen achieved adequately, with the result that there is a highprobability the subsequent movement stage will need to complete workintended for an earlier stage. Similarly, targeted movement mightovershoot desired positions especially in earlier stages so thatexpected actual movement is better controlled. This embodimentsacrifices the goal of minimizing round trip time in favor of achievinga higher probability of targeted end-stage outcome. This methodology isaccomplished within treatment plans specific to clusters of similarpatient cases.

Table 1 shows grouping of teeth in one embodiment. The sign conventionof tooth movements is indicated in Table 2. Different tooth movements ofthe selected 60 arches were demonstrated in Table 3 with performancesorted by descending order. The appliance performance can be broken into4 separate groups: high (79-85%), average (60-68%), below average(52-55%), and inadequate (24-47%). Table 4 shows ranking of movementpredictability. Predictability is broken into 3 groups: highlypredictable (0.76-0.82), predictable (0.43-0.63) and unpredictable(0.10-0.30). For the particular set of data, for example, the findingsare as follows:

1. Incisor intrusion, and anterior intrusion performance are high. Therange for incisor intrusion is about 1.7 mm, and for anterior intrusionis about 1.7 mm. These movements are highly predictable.

2. Canine intrusion, incisor torque, incisor rotation and anteriortorque performance are average. The range for canine intrusion is about1.3 mm, for incisor torque is about 34 degrees, for incisor rotation isabout 69 degrees, and for anterior torque is about 34 degrees. Thesemovements are either predictable or highly predictable.

3. Bicuspid tipping, bicuspid mesialization, molar rotation, andposterior expansion performance are below average. The range forbicuspid mesialization is about 1 millimeter, for bicuspid tipping isabout 19 degrees, for molar rotation is about 27 degrees and forposterior expansion is about 2.8 millimeters. Bicuspid tipping andmesialization are unpredictable, whereas the rest are predictablemovements.

4. Anterior and incisor extrusion, round teeth and bicuspid rotation,canine tipping, molar distalization, and posterior torque performanceare inadequate. The range of anterior extrusion is about 1.7millimeters, for incisor extrusion is about 1.5 mm, for round teethrotation is about 67 degrees, for bicuspid rotation is about 63 degrees,for canine tipping is about 26 degrees, for molar distalization is about2 millimeters, and for posterior torque is about 43 degrees. All areunpredictable movements except bicuspid rotation which is predictable.TABLE 1 Studied groups of teeth Teeth Incisors #7, 8, 9, 10, 23, 24, 25,26 Canines #6, 11, 22, 27 Bicuspids #4, 5, 12, 13, 20, 21, 28, 29 Molars#2, 3, 14, 15, 18, 19, 30, 31 Anteriors #6, 7, 8, 9, 10, 11, 22, 23, 24,25, 26, 27 Posteriors #2, 3, 4, 5, 12, 13, 14, 15, 18, 19, 20, 21, 28,29, 30, 31 Round #4, 5, 6, 11, 12, 13, 20, 21, 22, 27, 28, 29

TABLE 2 Sign convention of tooth movements Type of Movement Xtranslation (−) is lingual (+) is buccal (Expansion/ Constriction) Xrotation (Tipping) Upper & Lower (−) is distal (+) is mesial rightquadrants Upper & Lower (−) is mesial (+) is distal left quadrants Ytranslation (Mesialization/ Distalization) Upper left & Lower (−) isdistal (+) is mesial right quadrants Upper right & Lower (−) is mesial(+) is distal left quadrants Y rotation (−) is lingual (+) is buccalcrown (Torquing) crown Z translation (−) is intrusion (+) is extrusion(Intrusion/Extrusion) Z rotation (−) is clockwise (+) iscounterclockwise (Pure Rotation)

TABLE 3 Ranking of Performance Index of movement Performance SidePredict- Group Movement Model Index Effect ability Incisor IntrusionLinear 85% 0.03 0.82 Anterior Intrusion Linear 79% 0.03 0.76 CanineIntrusion Linear 68% −0.10 0.43 Incisor Torque Linear 67% 0.21 0.63Anterior Torque Linear 62% 0.15 0.56 Incisor Rotation Linear 61% −0.090.76 Bicuspid Tipping Linear 55% 0.35 0.27 Molar Rotation Linear 52%0.11 0.58 Posterior Expansion Linear 52% 0.11 0.48 BicuspidMesialization Linear 52% 0.00 0.30 Bicuspid Rotation Linear 47% 0.280.63 Molar Distalization Linear 43% 0.02 0.20 Canine Tipping Linear 42%0.10 0.28 Posterior Torque Linear 42% 1.50 0.28 Round Rotation Linear39% −0.14 0.27 Anterior Extrusion Linear 29% −0.02 0.13 IncisorExtrusion Linear 24% 0.02 0.10

TABLE 4 Ranking of movement predictability Performance Side Predict-Group Movement Model Index Effect ability Incisor Intrusion Linear 85%0.03 0.82 Anterior Intrusion Linear 79% 0.03 0.76 Incisor RotationLinear 61% −0.09 0.76 Incisor Torque Linear 67% 0.21 0.63 BicuspidRotation Linear 47% 0.28 0.63 Molar Rotation Linear 52% 0.11 0.58Anterior Torque Linear 62% 0.15 0.56 Posterior Expansion Linear 52% 0.110.48 Canine Intrusion Linear 68% −0.10 0.43 Bicuspid MesializationLinear 52% 0.00 0.30 Canine Tipping Linear 42% 0.10 0.28 PosteriorTorque Linear 42% 1.50 0.28 Bicuspid Tipping Linear 55% 0.35 0.27 RoundRotation Linear 39% −0.14 0.27 Molar Distalization Linear 43% 0.02 0.20Anterior Extrusion Linear 29% −0.02 0.13 Incisor Extrusion Linear 24%0.02 0.10

In one embodiment, data driven analyzers may be applied. These datadriven analyzers may incorporate a number of models such as parametricstatistical models, non-parametric statistical models, clusteringmodels, nearest neighbor models, regression methods, and engineered(artificial) neural networks. Prior to operation, data driven analyzersor models are built using one or more training sessions. The data usedto build the analyzer or model in these sessions are typically referredto as training data. As data driven analyzers are developed by examiningonly training examples, the selection of the training data cansignificantly affect the accuracy and the learning speed of the datadriven analyzer. One approach used heretofore generates a separate dataset referred to as a test set for training purposes. The test set isused to avoid overfitting the model or analyzer to the training data.Overfitting refers to the situation where the analyzer has memorized thetraining data so well that it fails to fit or categorize unseen data.Typically, during the construction of the analyzer or model, theanalyzer's performance is tested against the test set. The selection ofthe analyzer or model parameters is performed iteratively until theperformance of the analyzer in classifying the test set reaches anoptimal point. At this point, the training process is completed. Analternative to using an independent training and test set is to use amethodology called cross-validation. Cross-validation can be used todetermine parameter values for a parametric analyzer or model for anon-parametric analyzer. In cross-validation, a single training data setis selected. Next, a number of different analyzers or models are builtby presenting different parts of the training data as test sets to theanalyzers in an iterative process. The parameter or model structure isthen determined on the basis of the combined performance of all modelsor analyzers. Under the cross-validation approach, the analyzer or modelis typically retrained with data using the determined optimal modelstructure.

In one embodiment, the data mining software 3 (FIG. 1A) can be a“spider” or “crawler” to grab data on the database 2 (FIG. 1A) forindexing. In one embodiment, clustering operations are performed todetect patterns in the data. In another embodiment, a neural network isused to recognize each pattern as the neural network is quite robust atrecognizing dental treatment patterns. Once the treatment features havebeen characterized, the neural network then compares the input dentalinformation with stored templates of treatment vocabulary known by theneural network recognizer, among others. The recognition models caninclude a Hidden Markov Model (HMM), a dynamic programming model, aneural network, a fuzzy logic, or a template matcher, among others.These models may be used singly or in combination.

Dynamic programming considers all possible paths of M “frames” through Npoints, subject to specified costs for making transitions from any pointi to any given frame k to any point j at the next frame k+1. Because thebest path from the current point to the next point is independent ofwhat happens beyond that point, the minimum total cost [i(k), j(k+1)] ofa path through i(k) ending at j(k+1) is the cost of the transitionitself plus the cost of the minimum path to i(k). Preferably, the valuesof the predecessor paths can be kept in an M×N array, and theaccumulated cost kept in a 2×N array to contain the accumulated costs ofthe possible immediately preceding column and the current column.However, this method requires significant computing resources.

Dynamic programming requires a tremendous amount of computation. For therecognizer to find the optimal time alignment between a sequence offrames and a sequence of node models, it must compare most framesagainst a plurality of node models. One method of reducing the amount ofcomputation required for dynamic programming is to use pruning. Pruningterminates the dynamic programming of a given portion of dentaltreatment information against a given treatment model if the partialprobability score for that comparison drops below a given threshold.This greatly reduces computation.

Considered to be a generalization of dynamic programming, a hiddenMarkov model is used in the preferred embodiment to evaluate theprobability of occurrence of a sequence of observations O(1), O(2), . .. O(t), . . . , O(T), where each observation O(t) may be either adiscrete symbol under the VQ approach or a continuous vector. Thesequence of observations may be modeled as a probabilistic function ofan underlying Markov chain having state transitions that are notdirectly observable.

In the preferred embodiment, the Markov model is used to modelprobabilities for sequences of treatment observations. The transitionsbetween states are represented by a transition matrix A=[a(i,j)]. Eacha(i,j) term of the transition matrix is the probability of making atransition to state j given that the model is in state i. The outputsymbol probability of the model is represented by a set of functionsB=[b(j), where the b(j) term of the output symbol matrix is the functionthat when evaluated on a specified value O(t) returns the probability ofoutputting observation O(t), given that the model is in state j. Thefirst state is always constrained to be the initial state for the firsttime frame of the Markov chain, only a prescribed set of left to rightstate transitions are possible. A predetermined final state is definedfrom which transitions to other states cannot occur.

In one embodiment, transitions are restricted to reentry of a state orentry to one of the next two states. Such transitions are defined in themodel as transition probabilities. For example, a treatment patterncurrently having a frame of feature signals in state 2 has a probabilityof reentering state 2 of a(2,2), a probability a(2,3) of entering state3 and a probability of a(2,4)=1−a(2,2)−a(2,3) of entering state 4. Theprobability a(2,1) of entering state 1 or the probability a(2,5) ofentering state 5 is zero and the sum of the probabilities a(2,1) througha(2,5) is one. Although the preferred embodiment restricts the flowgraphs to the present state or to the next two states, one skilled inthe art can build an HMM model with more flexible transitionrestrictions, although the sum of all the probabilities of transitioningfrom any state must still add up to one.

In each state j of the model, the current feature frame may beidentified with one of a set of predefined output symbols or may belabeled probabilistically. In this case, the output symbol probabilityb(j) (O(t)) corresponds to the probability assigned by the model thatthe feature frame symbol is O(t). The model arrangement is a matrixA=[a(i,j)] of transition probabilities and a technique of computingB=[b(j) (O(t))].

In one embodiment, the Markov model is formed for a reference patternfrom a plurality of sequences of training patterns and the output symbolprobabilities are multivariate Gaussian function probability densities.The dental treatment information traverses through the featureextractor. During learning, the resulting feature vector series isprocessed by a parameter estimator, whose output is provided to thehidden Markov model. The hidden Markov model is used to derive a set ofreference pattern templates, each template representative of anidentified pattern in a vocabulary set of reference treatment patterns.The Markov model reference templates are next utilized to classify asequence of observations into one of the reference patterns based on theprobability of generating the observations from each Markov modelreference pattern template. During recognition, the unknown pattern canthen be identified as the reference pattern with the highest probabilityin the likelihood calculator.

The HMM template has a number of states, each having a discrete value.However, as treatment pattern features may have a dynamic pattern incontrast to a single value, the addition of a neural network at thefront end of the HMM in an embodiment provides the capability ofrepresenting states with dynamic values. The input layer of the neuralnetwork comprises input neurons. The outputs of the input layer aredistributed to all neurons in the middle layer. Similarly, the outputsof the middle layer are distributed to all output neurons, which outputneurons correspond one-to one with internal states of the HMM. However,each output has transition probabilities to itself or to other outputs,thus forming a modified HMM. Each state of the thus formed HMM iscapable of responding to a particular dynamic signal, resulting in amore robust HMM. Alternatively, the neural network can be used alonewithout resorting to the transition probabilities of the HMMarchitecture.

The output streams or results 4 of FIG. 1A are used as feedback inimproving dental appliance design and/or usage by doctors. For example,the data mining results can be used to evaluate performance based onstaging approaches, to compare appliance performance indices based ontreatment approaches, and to evaluate performance comparing differentattachment shapes and positions on teeth.

The ability to study tooth-specific efficacy and product performance forlarge clusters of treatment outcomes enables statistically significantcomparisons to be made between two or more populations of cases. In theevent that the two clusters studied contain differences in treatmentapproach, appliance design, or manufacturing protocol, the differencesseen in the performance of the product as exhibited by the data output,can be attributed to the approach, design, or manufacturing protocol.The end result is a feedback mechanism that enables either the clinicianor the manufacturer the ability to optimize the product design and usagebased on performance data from a significantly large sample size usingobjective measurable data.

The theory of orthodontic treatment is not universally agreed upon, andactual treatment and outcomes are subject to additional uncertainties ofmeasurement of patient variables, of relationships to unmeasured patientvariables, as well as of varying patient compliance. As a result,different clinicians might prefer different treatment plans for a singlepatient. Thus, a single treatment plan may not be accepted by everyclinician since there is no universally accepted “correct” treatmentplan.

The next few embodiments allow greater clinician satisfaction andgreater patient satisfaction by tailoring treatment parameters topreferences of clinicians. The system detects differences in treatmentpreferences by statistical observation of the treatment histories ofclinicians. For example, clinicians vary in how likely they would be toperform bicuspid extraction in cases with comparable crowding. Even whenthere is not a sufficient record of past treatments for a givenclinician, clustering may be performed on other predictor variables suchas geographical location, variables related to training, or size andnature of practice, to observe statistically significant differences intreatment parameters.

Data mining can discover statistically significant patterns of differenttreatment outcomes achieved by different clinicians for comparablepatients. For example, patient cases clustered together might havesystematically fewer complications with one clinician as compared toanother. Such a difference detected by the data mining tool might beused as a flag for feedback to the more poorly performing clinician aswell as a flag for solicitation of treatment differences used by thebetter performing clinician.

In one embodiment, clustering techniques are used with previouslycompleted cases to categorize treatment complications and outcomes.Probability models of risk are then built within each cluster. New casesare then allocated to the same clusters based on similarity ofpre-treatment variables. The risks within each cluster of patients withcompleted treatments are then used with new cases to predict treatmentoutcomes and risks of complications. High-risk patients are then flaggedfor special attention, possibly including additional steps in treatmentplan or additional clinical intervention.

In another embodiment, practitioners are clustered into groups byobserved clinician treatment preferences, and treatment parameters areadjusted within each group to coincide more closely with observedtreatment preferences. Practitioners without observed histories are thenassigned to groups based on similarity of known variables to thosewithin clusters with known treatment histories.

FIG. 1E shows an exemplary process for clusterizing practices. First,the process clusterizes treatment practice based on clinician treatmenthistory such as treatment preferences, outcomes, and demographic andpractice variables (20). Next, the system models preferred clinicalconstraints within each cluster (22). Next, the system assignsclinicians without treatment history to clusters in 20 based ondemographic and practice variables (24). In one embodiment, the systemperforms process 100 (see FIG. 2A) separately within each cluster, usingcluster-specific clinical constraints (26). Additionally, the systemupdates clusters and cluster assignments as new treatment and outcomedata arrives (28).

FIG. 1F shows another embodiment of a data mining system to generateproposed treatments. First, the system identifies/clusterizes patienthistories having detailed follow-up (such as multiple high-resolutionscans), based on detailed follow-up data, diagnosis, treatmentparameters and outcomes, and demographic variables (40). Within eachcluster, the system models discrepancies between intended position andactual positions obtained from follow-up data (42). Further, within eachcluster, the system models risk for special undesirable outcomes (44).At a second tier of clustering, patient histories with less detailedfollow-up data are clusterized based on available variables. Thesecond-tier clustering is partial enough that each of the larger numberof second tier clusters can either be assigned to clusters calculated in40 or else considered a new cluster (46). The system refines step 42models with additional records from step 46 clusters (48). It can alsorefine step 44 models with additional records from step 48 clusters(50). At a third tier of clustering, the system then assigns newpatients to step 46 clusters based on diagnosis, demographic, andinitial physical (52). Within each step 52 cluster, the system modelsexpected discrepancies between intended position and actual positions(54). From step 54, the system uses revised expected positioninformation where relevant (including 232 and 250, FIG. 2B) (67).Additionally, within each step 52 cluster, the system models risk forundesirable outcomes (56). From step 56, the system also flags casesthat require special attention and clinical constraints (as in 204 and160, FIGS. 2B and 2A) (69). The process then customizes treatment planto each step 52 cluster (58). Next, the system iteratively collects data(61) and loops back to identify/clusterize patient histories (40).Additionally, clusters can be revised and reassigned (63). The systemalso continually identifies clusters without good representation foradditional follow-up analysis (65).

In clinical treatment settings, it is not cost-effective to obtain orprocess the full high-resolution data possible at every stage of toothmovement. For example:

-   -   Patients may use several appliances between visits to        clinicians.    -   A given patient may submit only one set of tooth impressions.    -   Radiation concerns may limit the number of CT or X-Ray scans        used.    -   Clinicians generally do not have the time to report detailed        spatial information on each tooth at each visit.

Due to these and other limitations, treatment planning is necessarilymade based on partial information.

In one embodiment, missing information is approximated substantially bymatching predictive characteristics between patients and arepresentative sample for which detailed follow-up information iscollected. In this case, patients are flagged based on poorlyanticipated treatment outcomes for requests for follow-up information,such as collection and analysis of additional sets of tooth impressions.Resulting information is then used to refine patient clusters andtreatment of patients later assigned to the clusters.

In general, patient data is scanned and the data is analyzed using thedata mining system described above. A treatment plan is proposed by thesystem for the dental practitioner to approve. The dental practitionercan accept or request modifications to the treatment plan. Once thetreatment plan is approved, manufacturing of appliance(s) can begin.

FIG. 2A illustrates the general flow of an exemplary process 100 fordefining and generating repositioning appliances for orthodontictreatment of a patient. The process 100 includes the methods, and issuitable for the apparatus, of the present invention, as will bedescribed. The computational steps of the process are advantageouslyimplemented as computer program modules for execution on one or moreconventional digital computers.

As an initial step, a mold or a scan of patient's teeth or mouth tissueis acquired (110). This step generally involves taking casts of thepatient's teeth and gums, and may in addition or alternately involvetaking wax bites, direct contact scanning, x-ray imaging, tomographicimaging, sonographic imaging, and other techniques for obtaininginformation about the position and structure of the teeth, jaws, gumsand other orthodontically relevant tissue. From the data so obtained, adigital data set is derived that represents the initial (that is,pretreatment) arrangement of the patient's teeth and other tissues.

The initial digital data set, which may include both raw data fromscanning operations and data representing surface models derived fromthe raw data, is processed to segment the tissue constituents from eachother (step 120). In particular, in this step, data structures thatdigitally represent individual tooth crowns are produced.Advantageously, digital models of entire teeth are produced, includingmeasured or extrapolated hidden surfaces and root structures.

The desired final position of the teeth—that is, the desired andintended end result of orthodontic treatment—can be received from aclinician in the form of a prescription, can be calculated from basicorthodontic principles, or can be extrapolated computationally from aclinical prescription (step 130). With a specification of the desiredfinal positions of the teeth and a digital representation of the teeththemselves, the final position and surface geometry of each tooth can bespecified (step 140) to form a complete model of the teeth at thedesired end of treatment. Generally, in this step, the position of everytooth is specified. The result of this step is a set of digital datastructures that represents an orthodontically correct repositioning ofthe modeled teeth relative to presumed-stable tissue. The teeth andtissue are both represented as digital data.

Having both a beginning position and a final position for each tooth,the process next defines a tooth path for the motion of each tooth. Inone embodiment, the tooth paths are optimized in the aggregate so thatthe teeth are moved in the quickest fashion with the least amount ofround-tripping to bring the teeth from their initial positions to theirdesired final positions. (Round-tripping is any motion of a tooth in anydirection other than directly toward the desired final position.Round-tripping is sometimes necessary to allow teeth to move past eachother.) The tooth paths are segmented. The segments are calculated sothat each tooth's motion within a segment stays within threshold limitsof linear and rotational translation. In this way, the end points ofeach path segment can constitute a clinically viable repositioning, andthe aggregate of segment end points constitute a clinically viablesequence of tooth positions, so that moving from one point to the nextin the sequence does not result in a collision of teeth.

The threshold limits of linear and rotational translation areinitialized, in one implementation, with default values based on thenature of the appliance to be used. More individually tailored limitvalues can be calculated using patient-specific data. The limit valuescan also be updated based on the result of an appliance-calculation(step 170, described later), which may determine that at one or morepoints along one or more tooth paths, the forces that can be generatedby the appliance on the then-existing configuration of teeth and tissueis incapable of effecting the repositioning that is represented by oneor more tooth path segments. With this information, the subprocessdefining segmented paths (step 150) can recalculate the paths or theaffected subpaths.

At various stages of the process, and in particular after the segmentedpaths have been defined, the process can, and generally will, interactwith a clinician responsible for the treatment of the patient (step160). Clinician interaction can be implemented using a client processprogrammed to receive tooth positions and models, as well as pathinformation from a server computer or process in which other steps ofprocess 100 are implemented. The client process is advantageouslyprogrammed to allow the clinician to display an animation of thepositions and paths and to allow the clinician to reset the finalpositions of one or more of the teeth and to specify constraints to beapplied to the segmented paths. If the clinician makes any such changes,the subprocess of defining segmented paths (step 150) is performedagain.

The segmented tooth paths and associated tooth position data are used tocalculate clinically acceptable appliance configurations (or successivechanges in appliance configuration) that will move the teeth on thedefined treatment path in the steps specified by the path segments (step170). Each appliance configuration represents a step along the treatmentpath for the patient. The steps are defined and calculated so that eachdiscrete position can follow by straight-line tooth movement or simplerotation from the tooth positions achieved by the preceding discretestep and so that the amount of repositioning required at each stepinvolves an orthodontically optimal amount of force on the patient'sdentition. As with the path definition step, this appliance calculationstep can include interactions and even iterative interactions with theclinician (step 160). The operation of a process step 200 implementingthis step will be described more fully below.

Having calculated appliance definitions, the process 100 can proceed tothe manufacturing step (step 180) in which appliances defined by theprocess are manufactured, or electronic or printed information isproduced that can be used by a manual or automated process to defineappliance configurations or changes to appliance configurations.

FIG. 2B illustrates a process 200 implementing the appliance-calculationstep (FIG. 2A, step 170) for polymeric shell aligners of the kinddescribed in above-mentioned U.S. Pat. No. 5,975,893. Inputs to theprocess include an initial aligner shape 202, various control parameters204, and a desired end configuration for the teeth at the end of thecurrent treatment path segment 206. Other inputs include digital modelsof the teeth in position in the jaw, models of the jaw tissue, andspecifications of an initial aligner shape and of the aligner material.Using the input data, the process creates a finite element model of thealigner, teeth and tissue, with the aligner in place on the teeth (step210). Next, the process applies a finite element analysis to thecomposite finite element model of aligner, teeth and tissue (step 220).The analysis runs until an exit condition is reached, at which time theprocess evaluates whether the teeth have reached the desired endposition for the current path segment, or a position sufficiently closeto the desired end position (step 230). If an acceptable end position isnot reached by the teeth, the process calculates a new candidate alignershape (step 240). If an acceptable end position is reached, the motionsof the teeth calculated by the finite elements analysis are evaluated todetermine whether they are orthodontically acceptable (step 232). Ifthey are not, the process also proceeds to calculate a new candidatealigner shape (step 240). If the motions are orthodontically acceptableand the teeth have reached an acceptable position, the current alignershape is compared to the previously calculated aligner shapes. If thecurrent shape is the best solution so far (decision step 250), it issaved as the best candidate so far (step 260). If not, it is saved in anoptional step as a possible intermediate result (step 252). If thecurrent aligner shape is the best candidate so far, the processdetermines whether it is good enough to be accepted (decision step 270).If it is, the process exits. Otherwise, the process continues andcalculates another candidate shape (step 240) for analysis.

The finite element models can be created using computer programapplication software available from a variety of vendors. For creatingsolid geometry models, computer aided engineering (CAE) or computeraided design (CAD) programs can be used, such as the AutoCAD®. softwareproducts available from Autodesk, Inc., of San Rafael, Calif. Forcreating finite element models and analyzing them, program products froma number of vendors can be used, including the PolyFEM product availablefrom CADSI of Coralville, Iowa, the Pro/Mechanica simulation softwareavailable from Parametric Technology Corporation of Waltham, Mass., theI-DEAS design software products available from Structural DynamicsResearch Corporation (SDRC) of Cincinnati, Ohio, and the MSC/NASTRANproduct available from MacNeal-Schwendler Corporation of Los Angeles,Calif.

FIG. 3 shows a process 300 of creating a finite element model that canbe used to perform step 210 of the process 200 (FIG. 2). Input to themodel creation process 300 includes input data 302 describing the teethand tissues and input data 304 describing the aligner. The input datadescribing the teeth 302 include the digital models of the teeth;digital models of rigid tissue structures, if available; shape andviscosity specifications for a highly viscous fluid modeling thesubstrate tissue in which the teeth are embedded and to which the teethare connected, in the absence of specific models of those tissues; andboundary conditions specifying the immovable boundaries of the modelelements. In one implementation, the model elements include only modelsof the teeth, a model of a highly viscous embedding substrate fluid, andboundary conditions that define, in effect, a rigid container in whichthe modeled fluid is held. Note that fluid characteristics may differ bypatient clusters, for example as a function of age.

A finite element model of the initial configuration of the teeth andtissue is created (step 310) and optionally cached for reuse in lateriterations of the process (step 320). As was done with the teeth andtissue, a finite element model is created of the polymeric shell aligner(step 330). The input data for this model includes data specifying thematerial of which the aligner is made and the shape of the aligner (datainput 304).

The model aligner is then computationally manipulated to place it overthe modeled teeth in the model jaw to create a composite model of anin-place aligner (step 340). Optionally, the forces required to deformthe aligner to fit over the teeth, including any hardware attached tothe teeth, are computed and used as a figure of merit in measuring theacceptability of the particular aligner configuration. Optionally, thetooth positions used are as estimated from a probabilistic model basedon prior treatment steps and other patient information. In a simpleralternative, however, the aligner deformation is modeled by applyingenough force to its insides to make it large enough to fit over theteeth, placing the model aligner over the model teeth in the compositemodel, setting the conditions of the model teeth and tissue to beinfinitely rigid, and allowing the model aligner to relax into positionover the fixed teeth. The surfaces of the aligner and the teeth aremodeled to interact without friction at this stage, so that the alignermodel achieves the correct initial configuration over the model teethbefore finite element analysis is begun to find a solution to thecomposite model and compute the movement of the teeth under theinfluence of the distorted aligner.

FIG. 4 shows a process 400 for calculating the shape of a next alignerthat can be used in the aligner calculations, step 240 of process 200(FIG. 2B). A variety of inputs are used to calculate the next candidatealigner shape. These include inputs 402 of data generated by the finiteelement analysis solution of the composite model and data 404 defined bythe current tooth path. The data 402 derived from the finite elementanalysis includes the amount of real elapsed time over which thesimulated repositioning of the teeth took place; the actual end toothpositions calculated by the analysis; the maximum linear and torsionalforce applied to each tooth; the maximum linear and angular velocity ofeach tooth. From the input path information, the input data 404 includesthe initial tooth positions for the current path segment, the desiredtooth positions at the end of the current path segment, the maximumallowable displacement velocity for each tooth, and the maximumallowable force of each kind for each tooth.

If a previously evaluated aligner was found to violate one or moreconstraints, additional input data 406 can optionally be used by theprocess 400. This data 406 can include information identifying theconstraints violated by, and any identified suboptimal performance of,the previously evaluated aligner. Additionally, input data 408 relatingto constraints violated by, and suboptimal performance of previousdental devices can be used by the process 400.

Having received the initial input data (step 420), the process iteratesover the movable teeth in the model. (Some of the teeth may beidentified as, and constrained to be, immobile.) If the end position anddynamics of motion of the currently selected tooth by the previouslyselected aligner is acceptable (“yes” branch of decision step 440), theprocess continues by selecting for consideration a next tooth (step 430)until all teeth have been considered (“done” branch from step 430 tostep 470). Otherwise (“no” branch from step 440), a change in thealigner is calculated in the region of the currently selected tooth(step 450). The process then moves back to select the next current tooth(step 430) as has been described.

When all of the teeth have been considered, the aggregate changes madeto the aligner are evaluated against previously defined constraints(step 470), examples of which have already been mentioned. Constraintscan be defined with reference to a variety of further considerations,such as manufacturability. For example, constraints can be defined toset a maximum or minimum thickness of the aligner material, or to set amaximum or minimum coverage of the aligner over the crowns of the teeth.If the aligner constraints are satisfied, the changes are applied todefine a new aligner shape (step 490). Otherwise, the changes to thealigner are revised to satisfy the constraints (step 480), and therevised changes are applied to define the new aligner shape (step 490).

FIG. 5A illustrates one implementation of the step of computing analigner change in a region of a current tooth (step 450). In thisimplementation, a rule-based inference engine 456 is used to process theinput data previously described (input 454) and a set of rules 452 a-452n in a rule base of rules 452. The inference engine 456 and the rules452 define a production system which, when applied to the factual inputdata, produces a set of output conclusions that specify the changes tobe made to the aligner in the region of the current tooth (output 458).

Rules 452 a . . . 452 n have the conventional two-part form: an if-partdefining a condition and a then-part defining a conclusion or actionthat is asserted if the condition is satisfied. Conditions can be simpleor they can be complex conjunctions or disjunctions of multipleassertions. An exemplary set of rules, which defines changes to be madeto the aligner, includes the following: if the motion of the tooth istoo fast, add driving material to the aligner opposite the desireddirection of motion; if the motion of the tooth is too slow, add drivingmaterial to overcorrect the position of the tooth; if the tooth is toofar short of the desired end position, add material to overcorrect; ifthe tooth has been moved too far past the desired end position, addmaterial to stiffen the aligner where the tooth moves to meet it; if amaximum amount of driving material has been added, add material toovercorrect the repositioning of the tooth and do not add drivingmaterial; if the motion of the tooth is in a direction other than thedesired direction, remove and add material so as to redirect the tooth.

In an alternative embodiment, illustrated in FIGS. 5B and 5C, anabsolute configuration of the aligner is computed, rather than anincremental difference. As shown in FIG. 5B, a process 460 computes anabsolute configuration for an aligner in a region of a current tooth.Using input data that has already been described, the process computesthe difference between the desired end position and the achieved endposition of the current tooth (462). Using the intersection of the toothcenter line with the level of the gum tissue as the point of reference,the process computes the complement of the difference in all six degreesof freedom of motion, namely three degrees of translation and threedegrees of rotation (step 464). Next, the model tooth is displaced fromits desired end position by the amounts of the complement differences(step 466), which is illustrated in FIG. 5B.

FIG. 5D shows a planar view of an illustrative model aligner 60 over anillustrative model tooth 62. The tooth is in its desired end positionand the aligner shape is defined by the tooth in this end position. Theactual motion of the tooth calculated by the finite element analysis isillustrated as placing the tooth in position 64 rather than in thedesired position 62. A complement of the computed end position isillustrated as position 66. The next step of process 460 (FIG. 5B)defines the aligner in the region of the current tooth in this iterationof the process by the position of the displaced model tooth (step 468)calculated in the preceding step (466). This computed alignerconfiguration in the region of the current tooth is illustrated in FIG.5D as shape 68 which is defined by the repositioned model tooth inposition 66.

A further step in process 460, which can also be implemented as a rule452 (FIG. 5A), is shown in FIG. 5C. To move the current tooth in thedirection of its central axis, the size of the model tooth defining thatregion of the aligner, or the amount of room allowed in the aligner forthe tooth, is made smaller in the area away from which the process hasdecided to move the tooth (step 465).

As shown in FIG. 6, the process 200 (FIG. 2B) of computing the shape foran aligner for a step in a treatment path is one step in a process 600of computing the shapes of a series of aligners. This process 600 beginswith an initialization step 602 in which initial data, control andconstraint values are obtained.

When an aligner configuration has been found for each step or segment ofthe treatment path (step 604), the process 600 determines whether all ofthe aligners are acceptable (step 606). If they are, the process iscomplete. Otherwise, the process optionally undertakes a set of steps610 in an attempt to calculate a set of acceptable aligners. First, oneor more of the constraints on the aligners is relaxed (step 612). Then,for each path segment with an unacceptable aligner, the process 200(FIG. 2B) of shaping an aligner is performed with the new constraints(step 614). If all the aligners are now acceptable, the process 600exits (step 616).

Aligners may be unacceptable for a variety of reasons, some of which arehandled by the process. For example, if any impossible movements wererequired (decision step 620), that is, if the shape calculation process200 (FIG. 2B) was required to effect a motion for which no rule oradjustment was available, the process 600 proceeds to execute a modulethat calculates the configuration of a hardware attachment to thesubject tooth to which forces can be applied to effect the requiredmotion (step 640). Because adding hardware can have an effect that ismore than local, when hardware is added to the model, the outer loop ofthe process 600 is executed again (step 642).

If no impossible movements were required (“no” branch from step 620),the process transfers control to a path definition process (such as step150, FIG. 2A) to redefine those parts of the treatment path havingunacceptable aligners (step 630). This step can include both changingthe increments of tooth motion, i.e., changing the segmentation, on thetreatment path, changing the path followed by one or more teeth in thetreatment path, or both. After the treatment path has been redefined,the outer loop of the process is executed again (step 632). Therecalculation is advantageously limited to recalculating only thosealigners on the redefined portions of the treatment path. If all thealigners are now acceptable, the process exits (step 634). Ifunacceptable aligners still remain, the process can be repeated until anacceptable set of aligners is found or an iteration limit is exceeded(step 650). At this point, as well as at other points in the processesthat are described in this specification, such as at the computation ofadditional hardware (step 640), the process can interact with a humanoperator, such as a clinician or technician, to request assistance (step652). Assistance that an operator provides can include defining orselecting suitable attachments to be attached to a tooth or a bone,defining an added elastic element to provide a needed force for one ormore segments of the treatment path, suggesting an alteration to thetreatment path, either in the motion path of a tooth or in thesegmentation of the treatment path, and approving a deviation from orrelaxation of an operative constraint.

As was mentioned above, the process 600 is defined and parameterized byvarious items of input data (step 602). In one implementation, thisinitializing and defining data includes the following items: aniteration limit for the outer loop of the overall process; specificationof figures of merit that are calculated to determine whether an aligneris good enough (see FIG. 2B, step 270); a specification of the alignermaterial; a specification of the constraints that the shape orconfiguration of an aligner must satisfy to be acceptable; aspecification of the forces and positioning motions and velocities thatare orthodontically acceptable; an initial treatment path, whichincludes the motion path for each tooth and a segmentation of thetreatment path into segments, each segment to be accomplished by onealigner; a specification of the shapes and positions of any anchorsinstalled on the teeth or otherwise; and a specification of a model forthe jaw bone and other tissues in or on which the teeth are situated (inthe implementation being described, this model consists of a model of aviscous substrate fluid in which the teeth are embedded and which hasboundary conditions that essentially define a container for the fluid).

FIG. 7 is an exemplary diagram of a statistical root model. As showntherein, using the scanning processes described above, a scanned upperportion 701 of a tooth is identified. The scanned upper portion,including the crown, is then supplemented with a modeled 3D root. The 3Dmodel of the root can be statistically modeled. The 3D model of the root702 and the 3D model of the upper portion 700 together form a complete3D model of a tooth.

FIG. 8 shows exemplary diagrams of root modeling, as enhanced usingadditional dental information. In FIG. 8, the additional dentalinformation is X-ray information. An X-ray image 710 of teeth is scannedto provide a 2D view of the complete tooth shapes. An outline of atarget tooth is identified in the X-Ray image. The model 712 asdeveloped in FIG. 7 is modified in accordance with the additionalinformation. In one embodiment, the tooth model of FIG. 7 is morphed toform a new model 714 that conforms with the X-ray data.

FIG. 9 shows an exemplary diagram of a CT scan of teeth. In thisembodiment, the roots are derived directly from a high-resolution CBCTscan of the patient. Scanned roots can then be applied to crowns derivedfrom an impression, or used with the existing crowns extracted from ConeBeam Computed Tomography (CBCT) data. A CBCT single scan gives 3D dataand multiple forms of X-ray-like data. PVS impressions are avoided.

In one embodiment, a cone beam x-ray source and a 2D area detector scansthe patient's dental anatomy, preferably over a 360 degree angular rangeand along its entire length, by any one of various methods wherein theposition of the area detector is fixed relative to the source, andrelative rotational and translational movement between the source andobject provides the scanning (irradiation of the object by radiationenergy). As a result of the relative movement of the cone beam source toa plurality of source positions (i.e., “views”) along the scan path, thedetector acquires a corresponding plurality of sequential sets of conebeam projection data (also referred to herein as cone beam data orprojection data), each set of cone beam data being representative ofx-ray attenuation caused by the object at a respective one of the sourcepositions.

FIG. 10 shows an exemplary user interface showing the erupted teeth,which can be shown with root information in another embodiment. Eachtooth is individually adjustable using a suitable handle. In theembodiment of FIG. 10, the handle allows an operator to move the toothin three-dimensions with six degrees of freedom.

The teeth movement is guided in part using a root-based sequencingsystem. In one embodiment, the movement is constrained by a surface areaconstraint, while in another embodiment, the movement is constrained bya volume constraint.

In one embodiment, the system determines a surface area for each toothmodel. The system then sums all surface areas for all tooth models to bemoved. Next, the system sums all surface areas of all tooth models onthe arch. For each stage of teeth movement, the system checks that apredetermined area ratio or constraint is met while the tooth models aremoved. In one implementation, the constraint can be to ensure that thesurface areas of moving teeth are less than the total surface areas ofteeth on an arch supporting the teeth being moved. If the ratio isgreater than a particular number such as 50%, the system indicates anerror signal to an operator to indicate that the teeth should be movedon a slower basis.

In another embodiment, the system determines the volume for each toothmodel. The system then sums the volumes for all tooth models beingmoved. Next, the system determines the total volume of all tooth modelson the arch. For each stage of teeth movement, the system checks that apredetermined volume ratio or constraint is met while the tooth modelsare moved. In one implementation, the constraint can be to ensure thatthe volume for moving teeth is less than the volume of all teeth on anarch supporting the teeth being moved. If the ratio is greater than aparticular number such as 50%, the system indicates an error signal toan operator to indicate that the teeth should be moved on a slowerbasis.

Optionally, other features are added to the tooth model data sets toproduce desired features in the aligners. For example, it may bedesirable to add digital wax patches to define cavities or recesses tomaintain a space between the aligner and particular regions of the teethor jaw. It may also be desirable to add digital wax patches to definecorrugated or other structural forms to create regions having particularstiffness or other structural properties. In manufacturing processesthat rely on generation of positive models to produce the repositioningappliance, adding a wax patch to the digital model will generate apositive mold that has the same added wax patch geometry. This can bedone globally in defining the base shape of the aligners or in thecalculation of particular aligner shapes. One feature that can be addedis a rim around the gumline, which can be produced by adding a digitalmodel wire at the gumline of the digital model teeth from which thealigner is manufactured. When an aligner is manufactured by pressurefitting polymeric material over a positive physical model of the digitalteeth, the wire along the gumlines causes the aligner to have a rimaround it providing additional stiffness along the gumline.

In another optional manufacturing technique, two sheets of material arepressure fit over the positive tooth model, where one of the sheets iscut along the apex arch of the aligner and the other is overlaid on top.This provides a double thickness of aligner material along the verticalwalls of the teeth.

The changes that can be made to the design of an aligner are constrainedby the manufacturing technique that will be used to produce it. Forexample, if the aligner will be made by pressure fitting a polymericsheet over a positive model, the thickness of the aligner is determinedby the thickness of the sheet. As a consequence, the system willgenerally adjust the performance of the aligner by changing theorientation of the model teeth, the sizes of parts of the model teeth,the position and selection of attachments, and the addition or removalof material (e.g., adding wires or creating dimples) to change thestructure of the aligner. The system can optionally adjust the alignerby specifying that one or more of the aligners are to be made of a sheetof a thickness other than the standard one, to provide more or lessforce to the teeth. On the other hand, if the aligner will be made by astereo lithography process, the thickness of the aligner can be variedlocally, and structural features such as rims, dimples, and corrugationscan be added without modifying the digital model of the teeth.

The system can also be used to model the effects of more traditionalappliances such as retainers and braces and therefore be used togenerate optimal designs and treatment programs for particular patients.

FIG. 11 is a block diagram of the overall indexing system 1100 forpracticing the various embodiments of the present invention. Theindexing system 1100 in one embodiment includes a terminal 1101, whichmay be configured as a personal computer, workstation, or mainframe, andwhich includes a user interface input device 1103 and a user interfaceoutput device 1105, a storage unit 1107, and a central server 1109.

Referring to FIG. 11, the user interface input device 1103 may include akeyboard and may further include a pointing devices and/or a scanner,including x-ray or intra-oral scanner. The pointing device may be anindirect pointing device such as a mouse, trackball, touchpad, orgraphics tablet, or a direct pointing device such as a touchscreenincorporated into the user interface output device 1105. Other types ofuser interface input devices, such as voice recognition systems, may beused within the scope of the present invention.

Referring again to FIG. 11, the user interface output device 1105 mayinclude a printer and a display subsystem, which includes a displaycontroller and a display device coupled to the controller. The displaydevice may be a cathode ray tube (CRT), a flat-panel device such as aliquid crystal display, or a projection device. The display subsystemmay also provide nonvisual display such as audio output.

The indexing system 1100 shown in FIG. 11 also includes the data storageunit 1107 which is configured to, under the access and control of eithera central server 1109 or a client application, to maintain the basicprogramming and data constructs that provide the functionality of thepresent invention. Software is stored in storage unit 1107 which mayinclude a memory unit and file storage unit. The memory unit may includea main random access memory (RAM) for storage of instructions and dataduring program execution and a read-only memory (ROM) in which fixedinstructions are stored.

The file storage unit of the data storage unit 1107 may providepersistent (nonvolatile) storage for program and data files, andtypically includes at least one hard disk drive and at least one CD-ROMdrive (with associated removable media). There may also be other devicessuch as a floppy disk drive and optical drives (all with theirassociated removable media). Additionally, the file storage unit mayinclude drives of the type with removable media cartridges, such as harddisk cartridges and flexible disk cartridges. One or more of the drivesmay be located at a remote location, such as in central server 1109 on alocal area network or at a site on the Internet's World Wide Web or theentire system may be a stand-alone software application resident on theuser's system.

In one aspect of the present invention, the central server 1109 may beconfigured to communicate with the terminal 1101 and data storage unit1107 to access software stored in the data storage unit 1107 based onand in response to the input received from terminal 1101, and to performadditional processing based on procedures and/or routines in accordancewith the instructions or input information received from the terminal1101.

Referring back to FIG. 11, the indexing system 1100 in accordance withone embodiment of the present invention organizes orthodontic needs bythe most common configurations of orthodontic discrepancies in thedifferent dimensions: sagittal, vertical, horizontal/transverse, andarch length. The categories may be expanded to specifically captureother components such as facial profile, individual dentalconfigurations, dynamic functional relationships, and surrounding softtissue conditions; however, discrepancies in these four categoriescapture a significant portion of orthodontic related dental problems orconcerns. Within each category, there may be a predetermined number ofindividual components to characterize the potential conditions for thatdimension. For each condition, a predetermined combination of differentpossible conditions may be created. This collection of predefinedcombinations for each component, where each component belongs to one ofthe four main categories described, in one embodiment defines a matrixsuch that any patient at any time point may be defined as a specificaddress within the matrix. Both the matrix and address matrix may bestored in storage unit 1107.

FIG. 12 illustrates an exemplary tabular representation of the indexingsystem matrix stored in the storage unit 1107 of FIG. 11 in accordancewith one embodiment of the present invention. The exemplary table 1200of FIG. 12 illustrates a simplified version of the possible conditionsfor one component within each of the four categories.

Referring to FIG. 12, the table 1200 includes a category field 1201, areference component field 1202, and the pre-defined options field 1203.Table 1200 also includes a number of options field 1204. The categoryfield 1201 in one embodiment includes the categories for which referencedentition condition information is stored. In the exemplary embodiment,the categories may include: sagittal, vertical, horizontal, and archlength. In this exemplary embodiment, the reference component field 1202includes one common component within each dimension by whichmalocclusion is judged. The common pre-defined options field 1203includes the various levels of malocclusion for that dimension of thecategory. For example, the common malocclusions for the right caninecomponent of the sagittal category are: Full class 2+(greater than fullcusp Class 2), Full (Cusp) Class 2, Partial Class 2 (also called end-onClass 2), and so on. Within each dimensional component selection is alsoa selection for “normal.”

Referring to FIG. 12, the number of options field 1204 in one embodimentincludes the number of possible reference conditions in each category,and also a total number of possible combinations of referenceconditions. For example, the sagittal category has seven (7) possiblereference conditions for the canine relationship component and thevertical category has seven (7) reference conditions for the anterioroverbite component. The example shown yields 7×7×7×7=2401 possiblecombinations of reference conditions for the four components, as shownin table 1200 of FIG. 12. In one embodiment, each of these 2,401 patientcase combinations is stored in a database in storage unit 1107 (FIG.11), for example, by the central server 1109. Since there can benumerous components used to describe each of the four main orthodonticdimensions and not just one component per dimension as illustrated, inpractice, the total number of combinations that can be used to describea patient may be substantially higher, but at the same time, will be afinite number such that it may be indexed, catalogued, and queried asdescribed in FIG. 11.

In reference to the index table 1200 illustrated in FIG. 12, anidentifier may be composed of a four-position, or “four-bit” matrix:ABCD. In this four-bit matrix, in one embodiment of the presentinvention, the “A” position in the matrix corresponds to the sagittaldimension, the “B” position in the matrix corresponds to the verticaldimension, the “C” position in the matrix corresponds to the horizontaldimension, and the “D” position in the matrix corresponds to the archlength dimension.

The actual number or letter in the position of each “bit” of the matrixmay be associated with the corresponding condition within the category.For example, referring again to the exemplary table 1200 of FIG. 12, anidentifier of 3256 represents: a right canine partial Class 2, withmoderate anterior deep bite, upper midline to the left 0-1 mm, and lowermoderate crowding. This “3256” identifier corresponds to an address inan indexing database stored in storage unit 1107 which has stored in thedatabase, related clinical information for the particular pairing of“3256” to a user-defined treatment goal (for example, discussed infurther detail below with reference to FIG. 14).

Dental Characterization Database

Referring back to FIG. 11, the indexing system 1100 in one embodiment ofthe present invention may also be used to represent one or more teethwithin a patient's dentition. Typically an adult patient's dentitionincludes 32 teeth. Dentists usually characterize five surfaces of eachtooth: mesial, occlusal/incisal, distal, buccal/facial, and lingual.Each of these surfaces may be natural or covered by a restoration suchas silver amalgam, composite, porcelain, gold, or metal crown. The toothmay also be missing or have been treated with a root canal or animplant. These combinations may be represented with an indexing systemfor the initial dentition, target dentition (treatment goal), and finaldentition which is the outcome of the treatment.

For each tooth in a patient's dentition, there may be a number ofpossible conditions based on the characteristics of the tooth, such asthe surface of the tooth and whether the tooth as been treated or ismissing. The combinations of different possible conditions of the teethdefine a matrix. An exemplary embodiment of the present inventionincludes a 32-position address within the matrix, where each position inthe address corresponds to a tooth in a patient's dentition and includesa sub-address in which alphanumeric characters or other representationsrepresent the current condition of the tooth.

A “5-bit” sub-address for each tooth includes positions 12345 where eachof the positions “1” to “5” represents one of the five surfaces of thetooth. In particular, position 1 of the sub-address corresponds to themesial surface of the tooth, position 2 of the sub-address correspondsto the occlusal or incisal surface of the tooth, position 3 of thesub-address corresponds to the distal surface of the tooth, position 4of the sub-address corresponds to buccal or facial surface of the tooth,and position 5 of the sub-address corresponds to the lingual surface ofthe tooth.

Moreover, each of the following characters “A” to “N” corresponds to acondition of the particular surface of the tooth in the sub-address. A =amalgam B = composite C = porcelain veneer D = gold E = porcelain crownF = gold crown G = gold crown with root canal H = porcelain crown withroot canal I = amalgam with root canal J = composite with root canal K =gold crown with implant L = porcelain crown with implant M = missing N =natural

For example, consider the following patient identifier 1:NNABN. Theidentifier 1:NNABN would represent: tooth number 1 of a 32-bit addresswhich has a natural mesial surface (subaddress position 1), an occlusalamalgam (subaddress position 2), a natural distal surface (subaddressposition 3), a buccal/facial composite (subaddress position 4), and anatural lingual surface (subaddress position 5).

In an exemplary embodiment of patient's initial dentition, targetdentition (treatment goal), and final dentition, such example may beconfigured as:

TotalAddress=SubAddress1:SubAddress2:SubAddress3

SubAddress1=Teeth 1-32 initial

SubAddress2=Teeth 1-32 target

SubAddress3=Teeth 1-32 current, timepoint today

whereby each of the of the 1-32 may further include an additionsub-matrix of 1-5 surfaces as previously described.

In this manner, dentists may easily query their practice database todetermine how much dental work has been done and remains to be done.They can also track trends of use in their practice and what are themost common procedures in the practice. The patient matrix may also beused in forensics for patient identification purposes, as well as fornational security and other security purposes.

FIG. 13 illustrates an exemplary tabulation of the possible treatmentgoals of the indexing system treatment goal matrix stored in the storageunit 1107 of FIG. 11 in accordance with one embodiment of the presentinvention. Four examples of treatment goals are the following:

Treatment Goal 1: Pre-restorative set-up—the objective of this goal isto better position specific teeth for the purpose of improved placementof dental restorations such as crowns, bridges, and implants. Some ofthe patient's dental components may be left as is (untreated) if they donot contribute to the purpose of improvement of the restorative goal.

Treatment Goal 2: Esthetic alignment—the objective of this goal is toalign the patient's anterior teeth for the purpose of improvedesthetics. Generally speaking, the patient's bite may be left as is(untreated) if it does not contribute to the purpose of improving theesthetic component of the patient's smile.

Treatment Goal 3: Anterior function improvement—the objective of thisgoal is to improve the anterior function of the teeth while alsoimproving the anterior esthetic component. Generally speaking, thepatient's posterior occlusion may be left as is if it does notcontribute to the improvement of the canine function and/or anterioresthetics.

Treatment Goal 4: Optimal set-up—the objective of this goal is to makethe entire bite close to “textbook” ideal, including both the canine andmolar function.

FIG. 14 illustrates an expanded version of FIG. 13 using thecharacteristics as defined by the tabulation shown in FIG. 12. Morespecifically, each of the four treatment goals identified in FIG. 13 maybe further refined and formatted according to the tabulation andindexing shown in FIG. 12 to describe the target objective of treatmentin greater detail according to each individual component.

For example, for the treatment goal 1 for pre-restorative set-up, anexample of this goal according to the 4-bit matrix format in FIG. 12 maybe XXX4 where the “X” is the patient's existing relationship for thatcomponent left untreated, and only the fourth digit is planned fortreatment. Furthermore, for the treatment goal 2 for esthetic alignment,an example of this goal according to the 4-bit matrix format in FIG. 2may be XX44 where “X” is the patient's existing relationship for thatcomponent left untreated, and only the third and fourth digits(representing the transverse and arch length components, respectively)are planned for treatment.

In addition, for treatment goal 3 for anterior function improvement, anexample of this goal according to the 4-bit matrix format in FIG. 12 maybe 4X44 whereby “X” is the patient's existing relationship for thatcomponent left untreated. In this example, only the second digitcomponent (corresponding to the vertical dimension) is not planned fortreatment. Finally, for treatment goal 4 for optimal set-up, an exampleof this goal according to the 4-bit matrix defined in FIG. 12, may be4444.

There are various ways to generate an identifier which represents apatient's unique problem or case type. Traditionally, the method hasbeen to describe and define a characteristic and have the trainedindividual subjectively identify the condition or “label” which bestrepresents the patient's condition. To reduce the variability in thismethod requires calibration and/or objective measures to define each ofthe labels.

Another method involves using a visual image-based interface. Tocharacterize a patient's dentition, a user compares the patient'sdentition to images of reference dentition conditions which depict theseverity of malocclusion, or lack thereof. The user then identifieswhere the patient's dentition condition falls within a range ofreference conditions depicting malocclusion and selects the image thateither best represents the patient, or selects a relative position ofthe patient's condition from a continuous gradient of patient imagedepictions of the specific problem. The visual image interface can bepresented to the user without any descriptions or labels to avoid anypre-conceived biases associated with the label.

Visual images have been previously described in the ICON indexing systemfor example, to describe an esthetic component of the patient. In theICON system, the assessor selects 1 of 10 images which best representsthe patient's anterior esthetic component. Through calibration, multipleusers are then able to determine a patient's esthetic component withreasonable consistency. The use of a visual interface to capture everycomponent of the patient's orthodontic dental condition however, has notpreviously been described as an interface for creation of a digitalpatient database.

FIG. 15 illustrates the lower arch length component 1500 for use in theindexing system in accordance with one embodiment of the presentinvention. This illustration of the lower arch length component 1500 isan exemplary visual scale allowing the user to select an image which issimilar to the patient's dentition condition. Referring to FIG. 5, thereare shown seven images of the lower arch, each representing a possiblereference condition for the lower arch length category. In thisexemplary embodiment, images 1501-1507 represents the 7 imagescorresponding to the individual fields for the “Lower Arch Length”component of “Arch Length” dimension of FIG. 12. The user simply selectswhich of the seven images is best represented in the patient. Or theymay be able to select where in between two adjacent images the patientcan be best described. They do not need to know what the technical labelor term is; they simply need to select an image or area between twoimages based on direct comparison of the existing condition to thepictures presented.

In the exemplary embodiment shown in FIG. 15, each of the seven images1501-1507 has a corresponding predefined alphanumeric character. Thus,when an image is selected, the associated predefined alphanumericcharacter is added to the identifier address of the patient. By labelingeach category with an alphanumeric character, the patient's dentitionmay be characterized through alphanumeric addressing. The output to theuser may explain the specific details of their selection in greaterdetail, including the technical description and treatment optionsassociated with such a condition. In an alternate embodiment, analphanumeric character may be generated when the user selects the areain between adjacent images, representing that the patient's conditionfalls in between the condition of the adjacent images selected. The userinterface may also be a combination of both direct selection of theimage as well as in-between selection of images.

Referring now to FIG. 16, an exemplary doctor and patient informationdisplay 1600 for the indexing system 1100 is illustrated in accordancewith one embodiment of the present invention. This display 600 includesinformation input by a user into fields 1601-1603 to identify a patient.In particular, a patient's name is input into field 1601, a patient'sgender is input into field 1602, and a patient's primary concern(s) isinput into field 1603. The preferred embodiment of field 1603 is acheck-box selection of pre-defined possible conditions which can then becatalogued according to the selections of the user. It will beappreciated that other patient information may be added. Once thepatient information has been entered, a user can select a predefinedinput command or button to move onto the next display, which isillustrated in FIG. 17.

Referring to FIG. 17, an exemplary selection process display 1700 isshown for the sagittal dimension (matrix address position “A” in FIG.12)—right buccal, right canine/cuspid component. A series of images ofreference dentition conditions 1701-1703 are displayed in conjunctionwith buttons 1704 allowing the images to be scrolled to the left orright. A user clicks the left or right arrow buttons 1704 to select theimage of the reference dentition condition that best reflects thepatient's current condition specifically at the location(s) indicated bythe focusing arrows indicated in 1702. In this exemplary embodiment, auser clicks the left or right arrow buttons to select the cuspid(canine) relationship that is similar to a patient's current occlusion.

Once the selection is made, the next button 1705 is pressed to move ontothe next screen. The exemplary selection process display 1700 alsoincludes buttons 1706-1709 to allow a user to go back, access aglossary, ask for advice, and save the information, respectively.

Referring to FIG. 18, an exemplary selection process display 1800 isshown for the sagittal category—left buccal, left cuspid component. Aseries of images of reference dentition conditions 1801-1803 aredisplayed in association with buttons 804 allowing the images to bescrolled to the left or right. A user clicks the left or right arrowbuttons 804 to select the image of the reference dentition conditionthat best reflects the patient's current condition. In this exemplaryembodiment, a user clicks the left or right arrow buttons to select thecuspid relationship that is similar to a patient's current occlusion.

Once the selection is made, the next button 1805 is pressed to move ontothe next display which is illustrated in FIG. 19. The exemplaryselection process display 1800 also includes buttons 1806-1809 to allowa user to go back, access a glossary, ask for advice, and save theinformation, respectively.

Referring to FIG. 19, an exemplary selection process display 1900 isshown for the vertical dimension (matrix address position “B” in FIG.12)—anterior overbite component. A series of images of referenceconditions 1901-1903 are displayed in conjunction with buttons 1904allowing the images to be scrolled to the left or right. A user clicksthe left or right arrow buttons 1904 to select the image of thereference dentition condition that best reflects the patient's currentcondition. In this exemplary embodiment, a user clicks the left or rightarrow buttons 1904 to select the anterior vertical overbite relationshipcomponent that is similar to a patient's degree of open or deep bite.

Once the selection is made, the next button 1905 is pressed to move ontothe next display, which is illustrated in FIG. 20. The exemplaryselection process display 1900 also includes buttons 1906-1909 to allowa user to go back, access a glossary, ask for advice, and save theinformation, respectively.

Referring to FIG. 20, an exemplary selection process display 2000 isshown for the horizontal/transverse dimension (matrix address position“C” in FIG. 12)—upper and lower midline components. An image 1010representing a reference dentition condition is altered by clicking theupper arrows 2001-2002 corresponding to the upper arch of the image2010, and by clicking the lower arrows 2003-2004 corresponding to thelower arch of the image 1010 to best match the midline of the image 2010to a patient's midline component relationship. Once the selection ismade, the next button 2005 is pressed to move onto the next display,which is illustrated in FIG. 21. The exemplary selection process display2000 of FIG. 20 also includes buttons 2006-2009 to allow a user to goback, access a glossary, ask for advice, and save the information,respectively.

Referring to FIG. 21, an exemplary selection process display 2100 isshown for the upper arch length category. An image of a referencedentition condition 2101 and descriptions of reference dentitionconditions 2102, 2103 are displayed in association with buttons 2104allowing the reference dentition condition image and descriptions to bescrolled to the left or right. A user clicks the left or right arrowbuttons 2104 to select the image or description of the referencedentition condition that best reflects the patient's current condition.In this exemplary embodiment, a user clicks the left or right arrowbuttons 2104 to select the image or description of the referencedentition condition that is similar to a patient's upper arch lengthfrom the occlusal view. In this particular embodiment, if there is bothcrowding and spacing present, a user is instructed to use the net amountof crowding or spacing, but it may be possible to have each aspectcaptured independently.

Again, once the selection is made, the next button 2105 is pressed tomove onto the next display which is illustrated in FIG. 22. Theexemplary selection process display 2100 also includes buttons 2106-2109to allow a user to go back, access a glossary, ask for advice, and savethe information, respectively.

Referring to FIG. 22, an exemplary selection process display 2200 isshown for the arch length dimension (matrix position “D” in FIG.12)—lower arch length component. An image of a reference dentitioncondition 2201 and descriptions of reference dentition conditions 2202,2203 are displayed in association with buttons 2204 allowing thereference dentition condition image and descriptions to be scrolled tothe left or right. A user clicks the left or right arrow buttons 2204 toselect the image or description of the reference dentition conditionthat best reflects the patient's current condition for the lower archlength component of arch length. In this exemplary embodiment, a userclicks the left or right arrow buttons 2204 to select the image ordescription of the reference dentition condition that is similar to apatient's lower arch length from the occlusal view. In this example, ifboth crowding and spacing are present, the user is instructed to use thenet amount of crowding or spacing. It may be possible however to capturecrowding and spacing independently in order to derive the netdiscrepancy.

Once the selection is made, the next button 2205 is pressed to move ontothe next display, which is illustrated in FIG. 23. The exemplaryselection process display 2200 of FIG. 22 also includes buttons2206-2209 to allow a user to go back, access a glossary, ask for advice,and save the information, respectively.

FIG. 23 illustrates an exemplary patient summary tabulation 1300 foroutput display on terminal 1101 for use in the indexing system inaccordance with one embodiment of the present invention. The exemplarypatient summary display 2300 is generated from the information inputfrom previous displays 1600-2200, as illustrated in corresponding FIGS.16-22, respectively. Referring to FIG. 23, the selections made duringthe processes and displays described above and illustrated inconjunction with FIGS. 16-22 are summarized as shown in the summarydisplay 2300 in one embodiment of the present invention.

For example, for each reference dentition category including sagittal,vertical, horizontal and arch length, the corresponding malocclusionreference component (for example, right canine, anterior overbite, uppermidline relative to lower midline, and lower arch length, respectively),and each of which is associated with a selected one of the pre-definedoptions (for example, right canine partial Class 2, moderate anteriordeep bite, upper midline to left 0-1 mm, and lower moderate crowding,respectively). Also can be seen from FIG. 23 is the selected value ofthe selected pre-defined options 1203 (FIG. 12) as tabulated andillustrated in FIG. 12. The user is also able to edit the dentitioncondition information in each of the categories by selecting thecorresponding “EDIT” button to go back to the page desired andreselecting the image corresponding to that category.

In this manner, in one embodiment of the present invention, theinformation input by the user during the selection process is indexedand catalogued in a patient database (for example, the database 2400shown in FIG. 24 below) of the indexing system 1100. In one embodimentof the present invention, the selection process discussed in conjunctionwith FIGS. 16-22 for the indexing and cataloguing is transparent to theuser. The patient information input by the user in the selection processis used to generate both the summary display as illustrated in FIG. 23and an identifier representing the dentition conditions of the patient.FIGS. 16-22 illustrate the selection process display 1600 for use in theindexing system 1100 for various categories in accordance with oneembodiment of the present invention. This is the selection process forinputting a patient's dentition information. It will be appreciated thatalthough FIGS. 17-22 illustrate reference dentition conditionsrepresented by pictorial images, the present invention is not intendedto be limited to such representations. The reference dentitionconditions may also be represented by symbols, icons, descriptions,graphs, 3-D objects, radiographs, forms, and other types of images. Thereference conditions may also be user-defined through an interactivegraphical image such that the user best recreates the condition observedin the patient as a means of input for the system.

FIG. 24 illustrates a patient database 2400 for use in the indexingsystem 1100 in accordance with one embodiment of the present invention.The patient database 2400 includes a patient field 2401, an indexingdatabase address field 2402, and one or more category fields 2403. Inthe exemplary database of FIG. 24, the category fields 2403 include asagittal category field 2404, a vertical category field 2405, ahorizontal category field 2406, an upper arch length category field2407, a lower length category field 2408, a rotation field 2409, avertical correction field 2410, and a midline correction field 2411.

Referring to FIG. 24, the patient field 2401 includes the patient name.The indexing database address field 2402 includes the patientidentifier. This patient identifier corresponds to an address in theindexing database 1300, for example, as shown in FIG. 13. The address inthe indexing database 1300 is associated with treatment information forthat particular diagnostic combination. The category fields 2403, whichin this exemplary embodiment are the sagittal category field 2404, thevertical category field 2405, the horizontal category field 2406, theupper arch length category field 2407, the lower length category field2408, the rotation field 2409, the vertical correct field 2410, and themidline correct field 2411, include the patient's one or more dentitionconditions in the respective categories. For example, referring to FIG.24, patient L. Smith's dentition condition in the sagittal categoryfield 2404 is “Class I”. Patient M. Jones' dentition condition in theupper arch length category field 2407 is “normal”. The category fields2403 also indicate whether the particular reference condition iseligible for treatment (for example, shown by the Y/N indicator).

In this manner, the patient identifier may be configured to representthe patient conditions. For example, referring to the indexing databaseaddress field 2402, it is shown that L. Smith's identifier is“55772752”. Since the identifier includes eight positions, theidentifier is an eight-position matrix. The number in each position ofthe identifier represents a particular condition within a particularcategory. In this exemplary embodiment, the first position of theidentifier matrix represents the patient condition in the sagittalcategory. For example, the sagittal category field 2404 indicates thatL. Smith has a “Class I” malocclusion. Thus, the number 5 in the firstposition of the identifier represents a “Class I” malocclusion in thesagittal category.

Referring back to FIG. 24, the second position of the identifier matrixrepresents the patient condition in the vertical category. For example,the vertical category field 2405 indicates that L. Smith has normalocclusion. Thus, the number 5 in the second position of the identifierrepresents a normal occlusion in the vertical category. The thirdposition of the identifier matrix represents the patient condition inthe horizontal category. For example, the horizontal category field 2406indicates that L. Smith has a crossbite. Thus, the number 7 in the thirdposition of the identifier represents crossbite in the horizontalcategory.

Moreover, the fourth position of the identifier matrix represents thepatient condition in the upper arch length category. For example, theupper arch length category field 2407 indicates that L. Smith hasmoderate crowding. Thus, the number 7 in the fourth position of theidentifier represents moderate crowding in the upper arch lengthcategory. In addition, the fifth position of the identifier matrixrepresents the patient condition in the lower arch length category. Forexample, the lower arch length category field 2408 indicates that L.Smith has moderate spacing. Thus, the number 2 in the fifth position ofthe identifier represents moderate spacing in the lower arch lengthcategory.

In addition, the sixth position of the identifier matrix represents thepatient condition in the rotation category. For example, the rotationcategory field 2409 indicates that L. Smith has <20° rotation. Thus, thenumber 7 in the sixth position of the identifier represents <20°rotation in the rotation category. Further, the seventh position of theidentifier matrix represents the patient condition in the verticalcorrection category. For example, the vertical correct category field2410 indicates that L. Smith has no extrusion. Thus, the number 5 in theseventh position of the identifier represents no intrusion/extraction inthe vertical correction category.

Finally, referring yet again to FIG. 24, the eighth position of theidentifier matrix represents the patient condition in the midlinecorrect category. For example, the midline correct category field 2411indicates that L. Smith has >2 mm midline correction. Thus, the number 2in the eighth position of the identifier represents >2 mm midlinecorrect in the midline correction category.

In this manner, in one embodiment of the present invention, theconditions in the categories may be arranged in a predetermined ordereach associated with a numerical (for example “the number 2 in the eightposition of the identifier representing greater than 2 mm midlinecorrection in the midline correction category for patient L. Smith), ora predefined identifier such as, alphanumeric characters, symbols andthe like. In a further embodiment, the conditions in the categories maybe arranged in ascending order by difficulty and the categories aresorted in order of difficulty so that it is possible to define a matrixwhere 11111111 represents the mildest case and 33333333 is the mostsevere case in an eight position matrix identifier, for example asdescribed above. Additionally, each index in the matrix is weighted toderive a composite score of the overall case.

FIG. 25 illustrates an alternate embodiment of the present invention forcapturing an address in the selection process for use in the indexingsystem. FIG. 25 illustrates the table 1200 of FIG. 12 used directly as agraphical interface. In such embodiment, each reference condition asshown and illustrated in tabular format as rectangles may be representedas user input buttons with text which may be clicked to highlight andselect the appropriate reference condition. The assumption for this typeof interface is that the user understands the definitions of the text inorder to select the appropriate button. When the buttons are pressed toselect a particular reference condition, the selections are highlighted(shown in bold in FIG. 25). Clicking any button twice will deselect theinitial selection so that another selection can be made. In this manner,users who are more familiar with the various types of referenceconditions may be able to input the information more quickly thanthrough a visual-image based interface. In this example, the generatedaddress would be “3256.” The “Selected Value” column on the right sideof FIG. 25 is in one embodiment, transparent to the user/patient, andnot displayed to the user since the address has no relevance to the enduser, and is important only for the database query.

FIG. 26 illustrates an exemplary series of database addresses generatedby combining the initial condition address with the treatment goaladdress in one embodiment of the present invention. As indicated fromthe exemplary table 1200 of FIG. 12, there are 2,701 possible patientcase combinations or addresses for four components of seven possibleselection options each. Thus, an identifier address points to one of the2,701 possible combinations in the database. Each identifier isassociated with a field stored in a database of the storage unit 1107(FIG. 11). An identifier may be extended so that it represents thepatient's condition at different time points. For example, the databasemay be structured such that time points for initial dentition, targetdentition, and actual final dentition are captured as separateaddresses. For example, consider the following address:

-   -   ABCD: A*B*C*D*:A**B**C**D**

In this arrangement, the first four positions “A” to “D” of the matrixrepresent the patient's initial dentition (as previously described),positions “A*” to “D*” of the matrix represent the patient's targetdentition or treatment goal, and positions “A**” to “D**” of the matrixrepresent the patient's actual final dentition or treatment outcome.Because the number of positions in the matrix may be variable, and sinceeach position can include symbols, alphanumeric characters or otherrepresentations, the depth of individual patient cases that is stored ismay be detailed and specific to the patient and/or the associatedprofile or condition. Using the 4 possible treatment outcomesillustrated in FIG. 14 and the 2,701 possible combinations in FIG. 12,this equates to 2,701×4=10,804 possible paired combinations betweeninitial and goal.

FIG. 27 illustrates an exemplary database for a patient with an indexaddress of “3256” and the four possible treatment goals of 1 through 4.The resulting four combined addresses have different data for each ofthe parameters. This information is reported to the user either (1) uponcompletion of the case characterization, whereby all possible treatmentgoal options are presented to the user or (2) upon completion of thecase characterization and selection of a single treatment goal, wherebyonly the information from this address-goal pair is presented to theuser.

For each of these paired combinations, a combined address can becreated, with database assets in a “digital mailbox” associated witheach address. Assets for each digital mailbox can include, but is notlimited to: treatment plan information related to the case-treatmentgoal pairing, such as a text description of the treatment condition andgoals, treatment precautions, treatment length estimates, doctor skillset requirements, prescription data, sample case data, and casedifficulty. This data may be generated using expert opinion,computational algorithms, and/or historical case content.

For example, with respect to FIG. 23, where the case is identified as a“3256” and using the 4 types of treatment goals as shown in FIG. 14,combining the two yields four distinct database addresses: 3256:1,3256:2, 3256:3, and 3256:4. Each of the addresses can be populated withinformation specific to the case-treatment goal combination. All fouroptions can be simultaneously displayed to the user as “treatmentoptions” or the user can select a specific treatment goal and have asingle specific resulting treatment option data displayed. It is alsoconceivable that the user may also select any number of specific goals,and each of the data associated with each goal selected is reported tothe user depending on the initial condition parameters selected.

FIG. 28 illustrates a process 2800 for identifying a dentition problemor condition of a patient. The process 2800 is discussed more fully inconjunction with FIGS. 16-27. At step 2801, the user starts by enteringidentification information such as doctor and patient name, in additionto patient chief concern(s) (FIG. 16). In one embodiment, thiscomparison may be performed by the central server 1109 (FIG. 11) basedon information received, for example, from the terminal 1101, and/orbased on stored information retrieved from the data storage unit 1107.This and other related transactions in the process may be performed overa data network such as the internet via a secure connection. The userthen selects one of two user interfaces to input the patient's dentalcondition. The preferred method for the novice user is the visual-userinterface (FIG. 17-22) shown as step 2802. The advanced user will likelyprefer the alternative user interface (FIG. 25) illustrated as step2803.

Referring to FIG. 28, at step 2804 an initial dentition condition of apatient in each category is compared to one or more reference conditionsin the same category. After comparing the initial dentition condition ofthe patient in each category to one or more reference conditions foreach respective category, at step 2804, the selected reference conditionsimilar to the initial patient condition in the same category isreceived. Thereafter, at step 2805, the patient identifier is thengenerated based on the combination of alphanumeric characterscorresponding to the selected reference conditions. Edits can be made tothe inputs during the summary page review (step 2804) until the user issatisfied with the information submitted.

The output following the completion of the data input is a translationsummary (FIG. 23), which formats the user input into technicallyrelevant and correct terminology. At the same time, the user input isalso translated into a database address representing the current patientcondition (FIG. 25)—step 2805. Once the database address is created, theuser can choose to view all possible treatment options for this patient(OPTION 1), or specifically select a treatment goal and view thespecific goal associated with the user's selection (OPTION 2). To viewall the possible treatment options for the patient (OPTION 1), thedatabase (FIG. 27) is queried at step 2806, and all data associated withthe input address is presented to the user at step 2807 (END 1).

Referring back to FIG. 28, if the user desires to select a specificgoal, the specific goal is first defined by the user through a selectioninterface at step 2808 (FIG. 13), and the selection is then translatedinto a database address at step 2809 (FIG. 14), and the two addresses(patient condition and treatment goal) merged to create a combinedaddress or index at step 2810 (FIG. 26). This combined address is thenused to query the database at step 2811 (FIG. 27) in order to producedata specific to a single patient condition-treatment goal combinationat step 2812 (END 2).

For OPTION 2, it may also be possible that the user can select multiplegoals and only the data specific to those selected goals be produced forthe user. Once the user has reached END 1 or END 2, the user has theoption to purchase the product for the purpose of any one of theselected treatment goals, by selecting a pre-populated or semi-populatedtreatment prescription which can be part of the output data presented tothe user through this experience.

As discussed above, the user interface can provide one or more patientcases from the indexing database that matches the patient problem.Additionally, a range of patient cases from the indexing database thataddress specific components of the patient's problem can be provided. Inthis manner, in one embodiment of the present invention, search toolsmay be created to run statistics using the patient identifiers. Forexample, one search request may be to find all 131X cases. In thisexemplary search request, X represents any character in the fourthposition of the address. Thus, the search request would be to find allpatient identifiers having “131” as the first 3 digits of their patientidentifier address.

By labeling historically treated cases with this identificationmethodology, a catalog of orthodontic treatment can be created forfuture reference when planning treatment and assessing treatmentoutcomes. The result is a front-end user interface for capturing thedescription of an orthodontic condition and classifying the orthodonticcondition in a systematic scalable way. Referring again to FIG. 28, oncethe identifier is generated at step 2805, one or more treatment optionscan be determined using information generated from a database query. Thegenerated one or more treatment options may be stored in the datastorage unit 1107 (FIG. 11), and also, be provided to the terminal 1101for display on the display unit.

Given the diagnosis and treatment planning of orthodontic treatments caninclude a significant subjective component that may vary depending uponthe doctor's preferences and level of training, the indexing systemprovides a comprehensive, robust, and a substantially objective approachto establishing the patient diagnosis, treatment goal, and treatmentplan. The patient identifier of the present invention which representsthe patient's case, as well as the target treatment goal and finaloutcome enables treatment outcome profiles to be objectively catalogued,and for the catalog to be evaluated based on probabilities anddistributions. Indices such as prognosis and case difficulty can beassigned to matrix combinations, enabling similar cases to be treatedlike similarly successful cases. Treatment options may be correlated forcompleteness and ease of use. Treatment products, such as appliances,may be associated with specific matrix combinations so that theirsuggested use is more closely tied to a successful outcome.

Within the scope of the present invention, other embodiments forinputting a patient's dentition condition are also contemplated. Forexample, a configurable three-dimensional model may be used to input theinformation. In such embodiment, the user may recreate the patientdentition condition for the dimension. Alternatively, athree-dimensional graphics model may be staged to represent the entirerange of possible reference conditions for any given dimension. In suchembodiment, a user manipulates a slider to match a stage of the rangewhich is closest to the actual patient condition.

It will also be appreciated that this method of objectivelycharacterizing a case according to individual components is not limitedto the time points of pre-treatment, treatment goal, and post-treatment,and that any time point during treatment and following treatment may bealso catalogued in a similar fashion using the same input and databasesystem.

It will also be appreciated that in this exemplary embodiment althoughonly one reference condition is discussed as being selected for aparticular category, the present invention is not intended to be solimiting. The selection of one or more reference conditions within eachcategory is within the scope of the present invention.

Accordingly, a method for characterizing a dentition of a patient in oneembodiment of the present invention includes comparing an initialpatient condition in each of a plurality of dentition categories withone or more reference conditions in each of the plurality of dentitioncategories, where each of the one or more reference conditions has acorresponding representation, selecting at least one reference conditionin one or more of the plurality of dentition categories, where eachselected reference condition is similar to the initial patient conditionin a same dentition category, and generating a patient identifier basedon the corresponding representations of each selected referencecondition.

In one aspect, the plurality of dentition categories may include atleast two of: sagittal, vertical, horizontal, upper and arch lengthdimensions, or a number of a tooth in a dentition of a patient.

Moreover, the method may further include determining whether eachinitial patient condition is indicated for treatment based on treatmentinformation corresponding to the selected reference condition, providingone or more treatment options for each initial patient conditionindicated for treatment, where the one or more treatment options includeone or more of a treatment description, a treatment goal, a time tocomplete the treatment, a difficulty level, and a skill level tocomplete the treatment, an example of the treatment option.

Further, in another aspect, the method may also include comparing atleast a portion of the patient identifier with one or more referenceidentifiers, wherein each of the one or more reference identifiersincludes an initial reference dentition and a final reference dentition,selecting at least one reference identifier from the one or morereference identifiers, wherein the selected reference identifierincludes the portion of the patient identifier, and determining a finalpatient dentition based on the final reference dentition correspondingto the selected reference identifier.

A method for characterizing a dentition of a patient in accordance withanother embodiment of the present invention includes receiving aninitial dentition of a patient, generating an initial profilerepresenting the initial dentition of the patient, identifying aninitial malocclusion from the initial profile, and comparing at least aportion of the initial profile with one or more reference profiles ofreference dentitions, where said one or more reference profiles includesa reference malocclusion substantially similar to the initialmalocclusion at the beginning, during any treatment stage, or finaloutcome treatment position.

Also, the method may also include the step of selecting at least one ofthe one or more reference profiles, where said one or more referenceprofiles has a related final reference dentition.

Additionally, in a further aspect, the method also includes providing atarget dentition of the patient based on the final reference dentition.

The step of generating an initial profile in one embodiment may includevisually categorizing the initial dentition of the patient.

Moreover, the method may also include identifying one or more treatmentoptions associated with the one or more reference profiles.

A system for providing an orthodontic profile indexing system inaccordance with still another embodiment of the present inventionincludes a storage unit, and a controller unit operatively coupled tothe storage unit, and configured to compare an initial patient conditionin each of a plurality of dentition categories with one or morereference conditions in each of the plurality of dentition categories,where each of the one or more reference conditions has a correspondingrepresentation, select at least one reference condition in one or moreof the plurality of dentition categories, where each selected referencecondition is similar to the initial patient condition in a samedentition category, and to generate a patient identifier based on thecorresponding representations of each selected reference condition.

The controller unit may be configured to determine whether each initialpatient condition is eligible for treatment based on treatmentinformation corresponding to the selected reference condition, and toprovide one or more treatment options for each initial patient conditioneligible for treatment.

Also, the controller unit may be further configured to compare at leasta portion of the patient identifier with one or more referenceidentifiers, where each of the one or more reference identifiersincludes an initial reference dentition and a final reference dentition,to select at least one reference identifier from the one or morereference identifiers, where the selected reference identifier includesthe portion of the patient identifier, and to determine a final patientdentition based on the final reference dentition corresponding to theselected reference identifier.

In addition, a terminal may be operatively coupled to the controllerunit, and configured to transmit one or more of the initial patientcondition, where the terminal may be further configured to include adisplay unit.

A system for characterizing a dentition of a patient in accordance withstill another embodiment of the present invention includes a centralcontroller unit configured to generate an initial profile representingthe initial dentition of the patient, to identify an initialmalocclusion from the initial profile, and to compare at least a portionof the initial profile with one or more reference profiles of referencedentitions, wherein said one or more reference profiles includes areference malocclusion substantially similar to the initialmalocclusion.

In another aspect, a user terminal may be operatively coupled to thecentral controller unit, the user terminal configured to transmit theinitial dentition of the patient.

The central controller unit may be further configured to select at leastone of the one or more reference profiles, wherein said one or morereference profiles has a related final reference dentition.

In addition, the central controller unit may be further configured toprovide a target dentition of the patient based on the final referencedentition.

The central controller unit may be further configured to visuallycategorize the initial dentition of the patient.

Moreover, the central controller unit may be further configured toidentify one or more treatment options associated with the one or morereference profiles.

In yet still a further aspect, a storage unit may be configured to storeone or more of an initial profile an initial malocclusion, and areference malocclusion.

The various processes described above including the processes performedby the central server 1109 (FIG. 11) in the software applicationexecution environment in the indexing system 1100 including theprocesses and routines described in conjunction with the Figures may beembodied as computer programs developed using an object orientedlanguage that allows the modeling of complex systems with modularobjects to create abstractions that are representative of real world,physical objects and their interrelationships. The software required tocarry out the inventive process, which may be stored in the memory ordata storage unit 1107 of the indexing system or internally (not shown)within the central server 1109, may be developed by a person of ordinaryskill in the art and may include one or more computer program products.

While the characterization of adult dentition has been discussed inconjunction with the embodiments described above, the variousembodiments of the present invention may be used for thecharacterization of child dentitions. In addition, in accordance withthe embodiments of the present invention, the various aspects of thepresent invention may be manually implemented by the user, for example,using print-out documentation, visual graphics, and/or photographicimages of the conditions and/or treatment options, and further, mayinclude, within the scope of the present invention, manual computationor calculation of the results. In this manner, within the scope of thepresent invention, the various embodiments discussed above in thecontext of a computerized system for implementing the aspects of thepresent invention, may be implemented manually.

FIG. 29 is an example user interface display for initiating sampleorthodontic case assessment in accordance with one embodiment of thepresent invention. Referring to FIG. 29, in one embodiment, a user suchas a patient, a doctor or a clinician is provided a visual guideinterface (for example, using a display unit of a computer system) forinitiating a sample orthodontic case assessment. More specifically, theuser interface display 2900 in one embodiment includes a patient field2901 for entering information related to the patient, such as thepatient's name. Within the scope of the present disclosure, additionalpatient related data fields may be provided on the user interfacedisplay 2900. Referring to FIG. 29, also shown is a retrieve button 2902which is configured to retrieve a previously stored profile, if it hasbeen previously stored in the one or more databases, of the patientwhose information has been entered in the patient field 2901.Thereafter, pressing a next button 2903 on the user interface display2900 in one embodiment changes the displayed information on the userinterface display 2900 to the next page or display as shown, forexample, in conjunction with FIG. 30 below.

FIG. 30 is an example user interface display for providing patientdesired orthodontic treatment information in accordance with oneembodiment of the present invention. Referring to FIG. 30, in oneembodiment, the user may be provided with a plurality of options toselect the patient's concern or orthodontic related complaint. Forexample, the display area 3001 in one embodiment of the user interfacedisplay 3000 may be configured to provide a plurality of orthodonticrelated conditions from which the user may select, such as, protrudedincisors, narrow smile, overlapped teeth, small teeth, spaced betweenteeth, underbite, or uneven smile. If none of the pre-specified anddisplayed conditions are pertinent to the user, then the user mayoptionally enter the patient's orthodontic related condition in theOther field shown in the user interface display 3000.

Upon selecting the relevant one or more orthodontic conditions, the usermay press the next button 3003 to proceed to the next stage in thevisual guide interface. Alternatively, if the user desires to return toa previously displayed user interface display, then the user may press aback button 3002 shown on the user interface display 3000. As shown inthe Figures, the next series of user interface displays illustrate aplurality of selection criteria for choosing the suitable orthodonticcondition of the patient using, for example, a combination of graphicalimages and corresponding text description as described in further detailin conjunction with FIGS. 31-34.

More specifically, FIGS. 31-34 are an example user interface displaysfor providing patient orthodontic condition information in accordancewith one embodiment of the present invention. Referring to FIG. 31, theuser interface display 3100 includes a first display area 3101displaying options for the patient to select the image of orthodonticrelated condition that most resembles the patient's condition. Morespecifically, in the first display area 3101 the user may select theimage that best represents the position of the patient's centrals andlaterals. Furthermore, referring again to FIG. 31, a second display area3102 is provided in the user interface display 3100 which illustrates aplurality of images that permits the user to select the most similaroverjet condition. It can be seen that, when the user selects one of theplurality of images from the second display area 3102, the selectedimage is displayed in a magnified manner in a predefined selection area3103 of the user interface display 3100.

As described in further detail below, the user may toggle between theplurality of images in the second display area 3102 which in oneembodiment changes the corresponding displayed image in the predefinedselection area 3103. In one embodiment, toggling between the differentimages in the second display area 3102 will change or replace thecorresponding image in the predefined selection area 3103 substantiallyin real time such that there is substantially no overlap of the twoimages within the predefined selection area 3103. In this case, the useror viewer of the images displayed in the predefined selection area 3103may temporarily visually retain the replaced image (displayed in thepredefined selection area 3103) such that when the new or toggled imageis displayed in the same redefined selection area 3101, the user orviewer perceives the difference between the two images within thepredefined selection area 3103.

In a further embodiment, the display change in the predefined selectionarea 3103 includes a predetermined time delay such that, when the usertoggles between the selection of different images in the second displayarea 3102, a predefined overlapping time period is established betweenthe image that is currently the predefined selection area, and the imagethat corresponds to the newly selected one of the plurality of images inthe second display area 3102. In this manner, the differences betweenthe various images in the second display area 3102 may be visuallydetermined. Accordingly, the user may be readily and easily ascertainthe differences between the plurality of images shown in the seconddisplay area 3102 by simple toggle selection between the plurality ofimages, and may be able to more accurately select the image whichcorresponds to the patient's orthodontic condition.

Referring to FIGS. 32-34, additional plurality of images related toother orthodontic conditions is presented on the user interface display3200, 3300, 3400. For example, FIG. 32 illustrates a plurality of images3201 which show various different states of an overbite condition, FIG.33 illustrate pluralities of images 3301, 3303 which show variousdifferent states of the midline to face condition and lower midline toupper midline conditions, respectively, and further, where each userinterface display 3200, 3300 include a corresponding predefinedselection area 3202, 3302, and 3304, respectively, that provide themagnified view of the selected image in the corresponding user interfacedisplay 3200, 3300. In addition, FIG. 34 illustrates pluralities ofimages 3401, 3403 related to teeth spacing/crowding conditions for upperarch and lower arch, respectively. Moreover, there are provided in theuser interface display 3400 a corresponding predefined selection area3402, 3404 to display the associated selected one of the plurality ofimages 3401, 3403 for the upper arch spacing/crowding condition and thelower arch spacing/crowding condition.

Referring again to FIGS. 32-34, each user interface display 3200, 3300,3400 is provided with a back button 3203, 3305, 3405, and a next button3204, 3306, 3406, which may be pressed by the user to advance to thesubsequent display or return to a previous display in the visual guideinterface. In this manner, using visual images (and optionally incombination with textual description), the user may capture patient'sorthodontic conditions. While not shown, in one embodiment the userselection of each image or orthodontic condition via the user interfacedisplays as shown in FIGS. 31-34 are stored in the one or more databasesassociated with the patient.

FIGS. 35A-35C are example user interface displays illustrating imageselection and associated enlarged display at a predetermined area of thedisplay in accordance with one embodiment of the present invention.Referring to FIGS. 35A-35C, the modification to the predeterminedselection area 3402 in the user interface display 3400 is shown infurther detail. That is, as the selection of one of the plurality ofimages 3401 moves from image 3410, to image 3420 and then to image 3430,the corresponding displayed magnified image in the predeterminedselection area 3402 is correspondingly changed to display the selectedone of image 3410, image 3420 or image 3430.

In one embodiment, the display of the selected one of the plurality ofimages 3401 may include a predetermined overlap such that, an overlap inthe displayed image in the predetermined selection area 3402 of thecurrent selected image and the new image to replace the current selectedimage. In particular embodiments, the current selected image may befurther manipulated to be displayed in a varying degrees or percentagesof translucency such that an overlay of the new image over thetranslucent current selected image in the predetermined selection area3402 provides visually accurate differences between the two images. Thecontrast or degree of translucency or may be modified for either of thecurrent selected image or the new image, or both so as to effectivelyhighlight or visually present the image differences displayed in thepredetermined selection area 3402. In another aspect, the displayedimages in the predetermined selection area 3402 may include otherdisplay properties including, for example, a shadow profile, an outlineprofile, or any other suitable image enhancement or manipulation toillustrate differences between two or more images.

In still a further aspect, as discussed above, a selection changebetween the plurality of images 3401 at a predetermined speed by theuser may provide sufficient visual registration in the user's memory sothat the differences between the images in the predetermined selectionarea 3402 are readily perceived. In one aspect, the overlay or togglingof images to re-enforce or highlight the comparisons between images forimproved analysis may be applied to other areas such as, for example incomparison of celestial photography to identify bodies in motion,analysis of satellite images, comparison of intra-oral scan images toidentify movement, and any other areas where comparison of two or moreimages are desirable.

Referring now to FIG. 36, upon entering the patient related information(which may be optionally stored in the one or more databases associatedwith the patient), possible or applicable treatment options and theassociated parameters are determined. More specifically, FIG. 36 is anexample user interface display providing treatment goals associated withthe patient orthodontic condition information and patient desiredorthodontic treatment information in accordance with one embodiment ofthe present invention.

As shown, the user interface display 3600 in one embodiment isconfigured to display one or more treatment goals 3601 associated withthe patient and based upon the patient orthodontic condition providedand as described above in conjunction with FIGS. 32-34. Moreover, eachtreatment goal 3601 is further provided with one or more treatmentparameter information associated with implementing the correspondingtreatment goal. That is, for each treatment goal 3601 identified, acorresponding approximate number of aligners necessary for treatment isdisplayed in data field 3603, and moreover, a view sample button isprovided to retrieve a sample treatment plan associated with thetreatment of similar orthodontic case with the same or similar treatmentgoal identified.

For example, as shown in FIG. 36, pre-restorative setup is identified asone of the treatment goals 3601, and further, it is anticipated thatapproximately 6-12 aligners on average may be necessary to improve theposition of the mal-aligned crowns to better prepare for restorativeprocedure. Other treatment goals identified may include anteriororthodontic alignment that includes the alignment of the upper and poweranterior teeth, anterior function which may include improvement of thecanine relationship in addition to aesthetic alignment, and further,correct to ideal treatment goal which may include correction ofsubstantially all of the patient's malocclusions. Also, the userinterface display 3600 is also provided with a back button 3604 toreturn to a previous user interface display, or alternatively, the usermay press an exit button 3605 to complete the initial orthodontic caseassessment.

Referring back to FIG. 36, when the user presses one of the view samplebuttons 3602, a sample orthodontic case that was previously treated (forexample, treated to completion), is retrieved based upon the patientspecific parameters provided, and the selected treatment goal. Morespecifically, FIG. 37 is an example user interface display providing asimilar sample treatment case corresponding to the selected treatmentgoal for the patient orthodontic condition information in accordancewith one embodiment of the present invention. As shown, samplehistorical orthodontic case information is provided on the userinterface display 3700 with parameters and characteristics that aresimilar to the provided patient's conditions, and based upon theselected treatment goal.

In this manner, users such as doctors, clinicians or patients may easilyand readily determine whether the patient's orthodontic conditionspreliminarily qualify for treatment using aligners such as Invisalign®aligners. In addition, based on information received from the profile ofthe similar case that has been treated using the aligners, the users mayeasily determine the treatment parameters including the approximatenumber of aligners necessary, the approximate treatment duration,difficulty of the treatment, associated level of real or perceived painrelated to the treatment, and any other relevant characteristics orparameters that would be useful to the user. Moreover, in the case theuser decides to proceed with the treatment with the aligners, theinformation provided during the initial case assessment as describedabove may be retrieved from the one or more databases, and thus the usermay not be required to reenter the information.

FIGS. 38A-38B illustrate a manual visual aid for patient orthodonticcondition assessment and related treatment difficulty level inaccordance with one embodiment of the present invention. Referring toFIGS. 38A-38B, a manual visual guide in one embodiment may be providedfor simple, qualitative and quantitative preliminary determination ofaligner treatment for dental conditions. More specifically, the manualvisual guide in one embodiment graphically provides orthodonticcondition information and associated treatment difficulty rating basedon the chosen or selected treatment goal. The difficulty rating in oneembodiment is provided visually including an alphanumeric indication andan associated graphical and color combination. For example, a difficultyrating that requires advanced skill set may be associated with a “3”including a black color in diamond shape. This and other difficultyrating indicators are shown in the rating section 3802 of the manualvisual aid.

Referring back to FIGS. 38A-38B, for each identified difficulty rating,there is also provided visual representation of orthodontic conditionsthat may be treated based on the skill level. In this manner, users suchas doctors and clinicians may quickly identify which orthodontic casesare relatively easier to treat and which cases are more challenging totreat using the aligners, as well as the expected level of experience intreating patients with the aligners. Referring again to the Figures, thesummary field 3801 is provided to allow the users to providecontemplated treatment summary information that is simple and easy touse.

In the manner described above, in particular embodiments, users maydetermine whether patient's orthodontic conditions qualify for treatmentusing aligners, and further, the users may obtain treatment informationassociated with the treatment such as the level of skills necessary toperform the treatment, the anticipated treatment duration period, thecost associated with the treatment. In one aspect, the initial patientorthodontic assessment may include a manual visual aid or a computerizedvisual guide interface system. Additionally, in the computerized visualguide interface system, there are provided one or more databases whichhave stored therein an index of patients and patient conditions andassociated treatments. In this manner, the users may be easily obtain apreliminary assessment of a particular patient's orthodontic conditionand the associated treatment information based upon, for example, thedesired one or more treatment goals.

FIG. 39 is an example user interface display for illustrating treatmentplan information in accordance with one embodiment of the presentinvention. Referring to FIG. 39, the user interface display 3900 in oneembodiment includes information for a particular patient's orthodontictreatment as determined by the patient's initial conditions and thedesired or selected one or more treatment goals. More specifically, theuser interface display 3900 in one embodiment is configured to displaydetailed treatment information including, for example, difficulty ratingor assessment associated with the treatment (shown for example, by theblack diamond shape with a difficulty rating of “3” shown in the userinterface display 3700).

As further shown in the user interface display 3900, for the selectedtreatment goal of esthetic alignment with the complex or difficultrating of advanced (corresponding to “3”), the anticipated difficultiesassociated with the movement in the case and the corresponding necessaryskills for using the aligners are provided. For example, referring toFIG. 39, extrusion of tooth #3, and rotations of tooth #15 and #26 areidentified, among others ad anticipated difficult movements in theesthetic alignment case. Moreover, as further shown in FIG. 39, theanticipated necessary skills for the treatment for esthetic alignmentincludes, among others, attachments, and extrusions, for example. Basedon the information provided, in the case where the user desires tochange one or more parameters related to the treatment, such asdifficulty rating and the associated required skill level, the user maymodify the complexity or difficulty rating for the treatment, andreceive, for example, the possible treatment options associated with themodified complexity or difficulty rating, for example, as discussedbelow in conjunction with FIG. 40.

FIG. 40 is an example user interface display for modifying a treatmentplan parameter in accordance with one embodiment of the presentinvention. Referring to FIG. 40, the user interface display 4000includes a modification section 4001 which in one embodiment providesoptions to the user to modify the current difficulty rating associatedwith the treatment. For example, as shown in FIG. 40, the current ratingof advanced (black diamond “3”) shown in a rating area 4002 informs theuser of the current complexity or difficulty rating. Moreover, themodification section 4001 in the user interface display 4000 in oneembodiment includes section options to modify the complexity rating andto receive information associated with the most achievable treatmentcorresponding to the modified complexity or difficulty rating.

In this manner, in one embodiment, the user may initially be providedwith the complexity rating associated with the treatment goal specified,and thereafter, the user may modify the difficulty rating associatedwith the treatment to receive information related to achievabletreatments based on the modified difficulty rating. In one embodiment,the modification request by the user may be stored in the one or moredatabases. In turn, the modified difficulty rating associated with aparticular patient treatment may be used to modify the underlyingtreatment plan for the treatment of the particular patient's orthodonticconditions.

FIG. 41 illustrates example treatment difficulty categories fororthodontic treatment plans in accordance with one embodiment of thepresent invention. Referring to FIG. 41, in one embodiment the treatmentdifficulty or complexity rating may be categorized into threelevels—easy case 4101, moderate case 4102, and advanced case 4103. Asshown, each of the three levels of case complexity may bevisually/graphically associated with one or more of a alphanumericdesignation (for example, a “1”, a “2” or a “3”), a color designation(green for easy case, blue for moderate case, and black for advancedcase, for example), a graphical designation (a circle for easy case, asquare for moderate case, and a diamond for advanced case). Moreover,each of the three levels of case complexity may be associated with thecorresponding treatment parameters such as, for example, difficulty ofmovements, minimum recommended certification level, or minimumrecommended experience level. In this manner, each treatment difficultylevel may be easily determined by the users for a given case assessment,and thereafter, the user may modify or adjust the treatment difficultyassociated with the treatment of the patient orthodontic conditions sothat the corresponding treatment options may be easily determined.

FIG. 42 is a block diagram illustrating an orthodontic self-assessmentsystem in accordance with one embodiment of the present invention.Referring to FIG. 42, the self-assessment system in one embodimentincludes a data network 4210 and a server terminal 4220 operativelycoupled to the data network 4210. Moreover, one or more client terminals4230 may be provided and operatively coupled to the data network 4210.In one embodiment, the one or more client terminals 4230 may include apersonal computer, a communication enabled booth or kiosk terminal foundin public areas such as shopping malls, parks, libraries, and otherlocations. In one embodiment, the server terminal 4220 may be configuredto communicate with the one or more client terminals 4230 over the datanetwork 4210 to receive information related to orthodontic conditions,and provide preliminary assessment related to the treatment options forthe orthodontic conditions.

In one embodiment, the client terminal 4230 may include a display unitsuch as a computer display which may be used to visually interact withthe user at the client terminal 4230 to prompt for the patient specificinformation related to the patient's orthodontic conditions. Using a webbrowser or other user interface mechanism on the display unit, forexample, the patient may input the required information, and based uponwhich, the server terminal 4220 may be configured to provide apreliminary assessment as to whether the orthodontic conditions may betreated with aligners, and if so, whether there are doctors orclinicians in the local area (or a selected or designated area) thathave the necessary skill level to perform the desired treatment. In oneembodiment, the patient may be provided with one or more qualifieddoctors or clinicians that are qualified to treat the patient'sorthodontic conditions.

Alternatively, the user may be provided with an option to be contactedby one or more doctors or clinicians (randomly predetermined or selectedby the user based on information associated with the one or moredoctors). In this case, the user may be prompted to consent to thedissemination of the information that the user has provided at theclient terminal 4230, and upon consent by the user, the user specificinformation received from the client terminal 4230 may be transmitted toone or more doctors or clinicians that are qualified to treat the user'sorthodontic conditions.

FIG. 43 illustrates an example user interface for receiving user dentalcondition information in the system of FIG. 42. Referring to FIG. 43,the user display interface 4300 may include a plurality of fields fordata input by the user. For example, the user may be prompted to providethe user's name information in the data field 4301. Further, as shown bythe display area 4302 prompting the user to select what the user wishesto treat, the user is also provided with a plurality of selectableorthodontic conditions shown in the display area 4303.

Referring to FIG. 43, each of the selectable orthodontic conditionsshown in the display area 4303 may include a text description of thecondition and/or a visual graphic description of the associatedcondition. For example, in one embodiment, for the crooked smilecondition, the text “Crooked Smile” may be followed by an image or anicon that is displayed along side the text and which show a display ofan example crooked smile. Furthermore, the client terminal 4230 in oneembodiment may include a mirror or a similar device which will assistthe user to visually inspect the user's dental characteristics wheninputting information related to the user's dental conditions.

Within the scope of the present invention, the number of prompts orquestions provided to the user may include more or less than the numberof questions or user input fields shown in FIG. 43. Moreover, the userinterface display 4300 in one embodiment of the client terminal 4230 mayinclude additional information, such as, for example, but not limitedto, the approximate treatment duration, approximate cost estimateassociated with the treatment, options related to the type of dentalappliances that may be used, and profile information of the doctors orclinicians that are qualified to perform the treatment.

Furthermore, in one embodiment, a summary of the preliminary userassessment may be provided at the client terminal 4230 (FIG. 42) in aprint out format or any other types of data transfer, including forexample, a wireless communication (for example, Bluetooth, infrared, andthe like) to the user's mobile telephone, a personal digital assistant,a pager, laptop computer, or any other type of data receiving devicesuch as a portable storage unit including, for example, a compact memorydevice.

In one embodiment, the summary of preliminary user assessment providedto the user, for example, at the client terminal 4230 (FIG. 42) mayinclude the final outcome of the treatment of the one or more dentalconditions or complaints which the user has identified. Morespecifically, the user may be provided with images displayed on theclient terminal 3240 of the what the user's would look like aftercompleting the dental treatment, for example, using Invisalign®aligners.

Referring back to FIGS. 42-43, in one embodiment, the user inputtedinformation may be provided to one or more qualified doctors orclinicians to whom the user has consented to share the information, forexample. In this case, the user information related to the user'sorthodontic conditions may be provided to the one or more qualifieddoctors or clinicians prior to the user's visit to the one or morequalified doctors or clinicians. In this case, the one or more doctorsor clinicians may be better informed of the patient's particularconditions so as to provide more efficient or effective counseling ortreatment information related to the treatment of the user's orthodonticconditions.

In still a further embodiment, the user may be provided with an optionto schedule an appointment with the selected doctor or clinician using,for example, a calendaring tool which has access to at least a portionof the appointment schedule of the qualified doctors or clinicians. Insuch a case, the user may be presented with an open schedule for theselected doctor or clinician from which, the user may select anappointment time. In one embodiment, the user selection of theappointment time is communicated (for example, by electronic mail, apage, or by adding an entry in the selected doctor's calendar) to theselected doctor or clinician, and further, the selected doctor orclinician may be provided with the user's inputted information which mayinclude, a treatment summary information preliminarily identifying theuser's primary dental treatment objective, the selection of one or moreconditions that the user has identified, and the treatment planinformation generated and provided to the user.

In yet another aspect, the user may input at the client terminal 4230(FIG. 42), for example, a request to be contacted by the selected one ormore qualified doctors or clinicians, which may be communicated to theselected one or more qualified doctor or clinicians for follow up.

FIG. 44 is a flowchart illustrating an orthodontic self-assessmentprocedure in accordance with one embodiment of the present invention.Referring to FIG. 44, at step 4410, one or more dental conditions areselected, for example, using the user interface display 4300 (FIG. 43).Thereafter, one or more treatment goal information associated with thedental conditions are received at step 4420. Upon selection of a desiredtreatment goal at step 4430, treatment summary information is receivedat step 4440. In one embodiment, the treatment summary information mayinclude one or more of a visual display on a client terminal or a paperprint out including the patient specific information such as thepatient's conditions, the desired goal, and the options related to thetreatment such as, the type of appliances that may be used, theanticipated cost of treatment, list of qualified clinicians or doctorsthat may perform the treatment, and the like.

Referring back to FIG. 44, in one embodiment, the step of receivingtreatment goal associated with the dental condition may be bypassed, andinstead, after or at substantially the same as selecting the initialdental conditions, the desired treatment goal information may beprovided. In this manner, the user may not be required to have an indepth clinical understanding of the orthodontic conditions, but rather,using simple descriptive prompts in combination with visualrepresentation of dental conditions, the user may accurately determinethe user's dental conditions.

FIG. 45 is a flowchart illustrating an orthodontic self-assessmentprocedure in accordance with another embodiment of the presentinvention. Referring to FIG. 45, at step 4510, a new user or candidateaccess is detected. Thereafter, dental condition information is promptedfor input from the user at step 4520. In one embodiment, the newcandidate access request detected at step 4510 may optionally includeexisting candidate access request such that returning users that havealready provided user specific information may retrieve the existinguser profile instead of generating a new profile.

Referring to FIG. 45, at step 4530 one or more databases is queriedbased on the dental information received in response to the dentalcondition information prompt. That is, based on the user specific dentalcondition information, the one or more databases are searched to locateany previously treated (for example, treated to completion) cases thathave characteristics that are similar to the user's dental conditioninformation received. In one embodiment, the similarity of the user'sdental condition information or orthodontic condition compared to priortreated cases may be predefined to include certain parameters that areeither identical or substantially similar, while other parameters may bedefined to be less similar.

Referring again to FIG. 45, after the database query, one or moretreatment information based on the query is generated and output at step4540, for example to the client terminal 4230 (FIG. 42). Thereafter,optionally, additional treatment information selection may be received.That is, user provided selection of treatment information such as theselection of a particular doctor or a clinician, or the user consentinformation providing permission to share the user related informationincluding user dental condition information may be received at step4550. At step 4560, treatment summary information is generated andoutput for example, to the client terminal 4230 (FIG. 42).

In the manner described above, in one embodiment of the presentinvention, a client terminal may be located at a convenient location forpublic access, and further, wherein a user interface on the clientterminal may be provided to guide users with dental conditions or thoseseeking orthodontic treatment to perform a simple self-assessment todetermine a preliminary indication or determination of the appropriateand achievable orthodontic treatments.

FIG. 46 is a flowchart illustrating image selection process for patientorthodontic condition determination in accordance with one embodiment ofthe present invention. Referring to FIG. 46 and in conjunction withFIGS. 35A-35C, a first image selection is detected at step 4610.Thereafter, an enlarged image corresponding to the selected first imageis displayed at the predetermined display area, for example, in thepredefined selection area 3402 (FIGS. 35A-35C). At step 4630 a secondimage selection is detected, and thereafter, the displayed enlargedimage in the predetermined display area is replaced with an enlargedimage corresponding to the second selected image at step 4640. In oneembodiment, this routine may be repeated for additional image selection,and based upon which the predetermined display area may be configured torefresh or change the displayed enlarged image to correspond to the mostcurrent selected image.

In one embodiment, the predetermined display area may be configured torefresh or change the displayed enlarged image such that there issubstantially no temporal overlap between the current and new images fordisplay in the predetermined display area. Alternatively, thepredetermined display area may be configured to overlay or overlap thecurrent and the new images for a predetermined time period. In thismanner, within the scope of the present invention, the predetermineddisplay area may be configured to highlight or provide the differencesbetween the two images such that the user, during the image review andselection process, may be able to select the most accurate image whichcorresponds to the user's orthodontic condition.

FIG. 47 is a flowchart illustrating the treatment plan parametermodification in accordance with one embodiment of the present invention.Referring to FIG. 47, at step 4710 treatment plan informationcorresponding to a patient orthodontic condition and associatedtreatment goal is provided. Thereafter at step 4720 a modificationselection request is detected. That is, a request to change one or moreparameters associated with the provided treatment plan information (suchas, for example, the associated treatment difficulty rating) isdetected. Referring back to FIG. 47, based on the detected modificationselection request, at step 4730 modified treatment plan information isdetermined or generated. For example, if a modification selectionrequest for changing the treatment difficulty rating is detected at step4720, a corresponding modification to the treatment plan information isdetermined and thereafter, provided to the user at step 4740.

In one embodiment, the routine described above in conjunction with FIG.47 may be repeated based on the modification selection requestsdetected. With each modification selection request, correspondingtreatment plan information may be modified. In this manner, in oneembodiment of the present invention, users may be provided with a robustand dynamic system for assessing orthodontic conditions and treatmentoptions related to the orthodontic conditions.

In this manner, in one embodiment, the process of generating aprescription for orthodontic treatments may be simplified such that,using existing template information or generating an appropriatetemplate associated with a specific treatment goal, certain informationmay be retrieved and pre-filled into the prescription form template, forexample, the information that is associated with the patient's initialorthodontic condition, while other relevant information may be promptedfor input from the user. In one embodiment, the user may store theprescription information in the predefined template display format suchthat the user may retrieve the predefined template display for futuretreatment of similar types of cases. In a further aspect, the predefinedtemplate display may be associated with a particular one or more of anindexed or categorized value or score of the patient's initial dentalconditions, with the treatment goal, or with any other customizablecharacteristics, such that the user may retrieve the predefined templatedisplay for subsequent similar cases for treatment.

Systems and methods are disclosed providing a database comprising acompendium of at least one of patient treatment history; orthodontictherapies, orthodontic information and diagnostics; employing a datamining technique for interrogating said database for generating anoutput data stream, the output data stream correlating a patientmalocclusion with an orthodontic treatment; and applying the output datastream to improve a dental appliance or a dental appliance usage.

The achieved outcome, if measured, is usually determined using a set ofstandard criteria such as by the American Board of Orthodontics, againstwhich the final outcome is compared, and is usually a set of idealizednorms of what the ideal occlusion and bite relationship ought to be.Another method of determining outcome is to use a relative improvementindex such as PAR, IOTN, and ICON to measure degrees of improvement as aresult of treatment.

The present invention provides methods and apparatus for miningrelationships in treatment outcome and using the mined data to enhancetreatment plans or enhance appliance configurations in a process ofrepositioning teeth from an initial tooth arrangement to a final tootharrangement. The invention can operate to define how repositioning isaccomplished by a series of appliances or by a series of adjustments toappliances configured to reposition individual teeth incrementally. Theinvention can be applied advantageously to specify a series ofappliances formed as polymeric shells having the tooth-receivingcavities, that is, shells of the kind described in U.S. Pat. No.5,975,893, disclosure of which is incorporated herein by reference.

A patient's teeth are repositioned from an initial tooth arrangement toa final tooth arrangement by making a series of incremental positionadjustments using appliances specified in accordance with the invention.In one implementation, the invention is used to specify shapes for theabove-mentioned polymeric shell appliances. The first appliance of aseries will have a geometry selected to reposition the teeth from theinitial tooth arrangement to a first intermediate arrangement. Theappliance is intended to be worn until the first intermediatearrangement is approached or achieved, and then one or more additional(intermediate) appliances are successively placed on the teeth. Thefinal appliance has a geometry selected to progressively repositionteeth from the last intermediate arrangement to a desired final tootharrangement.

The invention specifies the appliances so that they apply an acceptablelevel of force, cause discomfort only within acceptable bounds, andachieve the desired increment of tooth repositioning in an acceptableperiod of time. The invention can be implemented to interact with otherparts of a computational orthodontic system, and in particular tointeract with a path definition module that calculates the paths takenby teeth as they are repositioned during treatment.

In general, in one aspect, the invention provides methods andcorresponding apparatus for segmenting an orthodontic treatment pathinto clinically appropriate substeps for repositioning the teeth of apatient. The methods include providing a digital finite element model ofthe shape and material of each of a sequence of appliances to be appliedto a patient; providing a digital finite element model of the teeth andrelated mouth tissue of the patient; computing the actual effect of theappliances on the teeth by analyzing the finite elements modelscomputationally; and evaluating the effect against clinical constraints.Advantageous implementations can include one or more of the followingfeatures. The appliances can be braces, including brackets andarchwires, polymeric shells, including shells manufactured by stereolithography, retainers, or other forms of orthodontic appliance.Implementations can include comparing the actual effect of theappliances with an intended effect of the appliances; and identifying anappliance as an unsatisfactory appliance if the actual effect of theappliance is more than a threshold different from the intended effect ofthe appliance and modifying a model of the unsatisfactory applianceaccording to the results of the comparison. The model and resultingappliance can be modified by altering the shape of the unsatisfactoryappliance, by adding a dimple, by adding material to cause anovercorrection of tooth position, by adding a ridge of material toincrease stiffness, by adding a rim of material along a gumline toincrease stiffness, by removing material to reduce stiffness, or byredefining the shape to be a shape defined by the complement of thedifference between the intended effect and the actual effect of theunsatisfactory appliance. The clinical constraints can include a maximumrate of displacement of a tooth, a maximum force on a tooth, and adesired end position of a tooth. The maximum force can be a linear forceor a torsional force. The maximum rate of displacement can be a linearor an angular rate of displacement. The apparatus of the invention canbe implemented as a system, or it can be implemented as a computerprogram product, tangibly stored on a computer-readable medium, havinginstructions operable to cause a computer to perform the steps of themethod of the invention.

Among the advantages of the invention are one or more of the following.Appliances specified in accordance with the invention apply no more thanorthodontically acceptable levels of force, cause no more than anacceptable amount of patient discomfort, and achieve the desiredincrement of tooth repositioning in an acceptable period of time. Theinvention can be used to augment a computational or manual process fordefining tooth paths in orthodontic treatment by confirming thatproposed paths can be achieved by the appliance under consideration andwithin user-selectable constraints of good orthodontic practice. Use ofthe invention to design aligners allows the designer (human orautomated) to finely tune the performance of the aligners with respectto particular constraints. Also, more precise orthodontic control overthe effect of the aligners can be achieved and their behavior can bebetter predicted than would otherwise be the case. In addition,computationally defining the aligner geometry facilitates direct alignermanufacturing under numerical control.

A computer-implemented method in one embodiment of the present inventionincludes projecting a first orthodontic related image at a predeterminedlocation within a display unit, selecting a second orthodontic relatedimage on the display unit, projecting the second orthodontic relatedimage at the predetermined area within the display unit such that adifference between the first orthodontic related image and the secondorthodontic related image is displayed at the predetermined area withinthe display unit.

In one embodiment, projecting the second orthodontic related image atthe predetermined area within the display unit may include projectingthe second orthodontic image within a predetermined time afterprojecting the first orthodontic image. Furthermore, projecting thesecond orthodontic image within the predetermined time after projectingthe first orthodontic image may include projecting the secondorthodontic image within a time that the difference between the firstand second orthodontic images is shown in the predetermined area.

Further, projecting the first orthodontic related image at thepredetermined area within the display unit may include projecting thefirst orthodontic related image during a first time period, andprojecting the second orthodontic related image at the predeterminedarea within the display unit may include projecting the secondorthodontic related image during a second time period.

The first and second time periods may be substantially non-overlapping.

The first orthodontic related image may be graphically associated withthe second orthodontic related image.

Also, projecting the first orthodontic related image may includeprojecting an enlarged state of the first orthodontic related image, andwherein projecting the second orthodontic related image includesprojecting an enlarged state of the second orthodontic related image.

The method may also include toggling between projecting the firstorthodontic related image and projecting the second orthodontic relatedimage such that a difference between the first and second orthodonticrelated image are displayed in the predetermined area.

The second orthodontic related image may be superimposed over the firstorthodontic related image in the predetermined area.

An apparatus in one embodiment of the present invention includes aninput device, and a display unit operatively coupled to the inputdevice, the display unit configured to display a first orthodonticrelated image at a predetermined area, the display unit furtherconfigured to replace the display of the first orthodontic related imageat the predetermined area with a second orthodontic related image inresponse to an input command received from the input device.

The second orthodontic related image displayed at the predetermined areawithin the display unit may be superimposed over the first orthodonticrelated image at the predetermined area.

The display unit may be configured to replace the display of the firstorthodontic related image with the second orthodontic related image suchthat the two images are substantially non-overlapping in thepredetermined area.

The display unit may be further configured to display an enlarged stateof the first orthodontic related image in the predetermined area, andfurther, wherein the display unit is further configured to display anenlarged state of the second orthodontic related image.

The display unit may be configured to replace the image displayed in thepredetermined area in response to the input command received from theinput device such that a difference between the first and secondorthodontic related image are shown in the predetermined area when thedisplayed images are being replaced.

Referring again to the Figures, FIG. 48 is an example user interface forproviding real time dynamic representation of orthodontic conditions inaccordance with one embodiment of the present invention. As shown, userinterface 4800 in one embodiment includes a first display segment 4810and a second display segment 4820, respectively corresponding to avisual representation of upper and lower teeth position. Within thescope of the present invention, fewer or additional display segments maybe provided on the user interface 4800, for example, to display only theupper or the lower teeth position, or alternatively, to displayadditional views of the user or lower teeth positions.

Referring again to FIG. 48, also shown in the user interface 4800includes a plurality of movement indicators 4811, 4812 corresponding tothe first display segment 4810, and a plurality of movement indicators4821, 4822 corresponding to the second display segment 4820. As shown,in one aspect, the selection (for example, using an input device of theuser interface 4800 such as a computer mouse, or input touchpad) of eachone of the plurality of movement indicators 4811, 4812, 4821, 4822 maybe configured to correspondingly reposition or move the display of theparticular image in the respective first or second display segment 4810,4820. For example, a selection of the movement indicator 4811 a in thefirst display segment 4810 is configured to correspondingly repositionthe display of the tooth 4813 as shown in the upward direction by apredetermined distance as shown within the first display segment 4810.Likewise, a selection of the movement indicator 4811 b in one aspect isconfigured to correspondingly reposition or move the display of thetooth 4813 is a downward direction by a predetermined distance.

In this manner, each tooth representation within the first displaysegment 4810 and the second display segment 4820 may be associated withone or more movement indicators 4811, 4812, 4821, 4822, including, forexample, directional arrows, icons, and the like to correspondinglyreposition or move the selected tooth within the first or second displaysegments 4810, 4820 in the desired direction. Accordingly, during thediagnosis of orthodontic conditions of a patient, or example, doctors orcare providers may be easily and visually represent and classify one ormore malocclusion of the patient's orthodontic condition. Moreover,while movement indicators are shown and described in FIG. 48, within thescope of the present invention, the user interface 4800 may beconfigured such that each tooth shown on the first or second displaysegment 4810, 4820 may be directly manipulated using, for example, aninput device such as a computer mouse, so that the selected toothposition may be visually manipulated to provide an accuraterepresentation of the patient's orthodontic condition.

Accordingly, in one embodiment, direct manipulation of the virtualrepresentation of a patient's dentition for malocclusion classification,among others, for purposes of pre-treatment assessment is provided. Inone aspect, the classification may be determined based upon a lookuptable which has stored therein classification information associatedeach type of malocclusion, and the category or classification of whichmay be determined based upon the selected movement of a particulartooth, for example, using the one or more movement indicators. Forexample, in one embodiment, the doctor or the user may be provided witha virtual model of a patient's dentition (for example, an anterior view)which may be directly manipulated using, for example, an input device ofthe user interface 4800 such that the virtual dentition displayed on theuser interface 4800 may be configured to provide an accuraterepresentation of the patient's actual dentition condition. Moreover,the input information based on the user's direct manipulation of thetooth images (for example, the selection information of the variousmovement indicators 4811, 4812, 4821, 4822, may be used forclassification of malocclusion for purposes of orthodontic treatmentassessment.

FIG. 49 is an example user interface for providing dynamic orthodonticcondition validation in accordance with one embodiment of the presentinvention. Referring to FIG. 49, user interface 4900 in one embodimentincludes a first display segment 4910 which provides a visualrepresentation of teeth positions. In one embodiment, each individualtooth shown in the first display segment 4910 is configured to beselectable using, for example, an input device such as a computer mouseor a touchpad input device of a computer terminal, for example. When auser selects a tooth, for example, tooth 4911 or tooth 4912, shown inthe first display 4910, in one embodiment, a corresponding image displaysegment 4920 or image display segment 4930 is also displayed on the userinterface 4900, where the image display segment 4920 or image displaysegment 4930 is configured to display the selected tooth 4911, 4912,respectively in the orthodontic condition represented.

That is, for example, when the user selects tooth 4911 on the firstdisplay segment 4910, a corresponding image display segment 4920 isadditionally displayed on the user interface 4900 showing the crossbitecondition of the selected tooth 4911. Likewise, when the user selectstooth 4912 in the first image segment 4910, a corresponding imagedisplay segment 4930 is additionally displayed on the user interface4900 that visually represents the crossbite condition of the selectedtooth 4912.

In this manner, in one embodiment, doctors or users are provided with adynamic validation of a predetermined orthodontic condition for aspecific or selected one or more teeth of a patient during theorthodontic condition assessment and diagnosis phase of orthodontictreatment.

While crossbite condition is described above in conjunction with FIG.49, within the scope of the present invention, other orthodonticconditions may be visually represented, including, but not limited tounderbite, overbite, overjet, spacing or crowding, arch shape, incisorprofile, inclination of posterior of upper or lower arch, bicuspid orcuspid rotation, missing tooth, or midline discrepancy. Indeed, in oneaspect, thumbnail type malocclusion image illustrating the condition ofone or more selected tooth is visually provided on the user interface4900 when the user or doctor selects one or more teeth in the firstdisplay segment 4910. The user or doctor is then able to confirm orvalidate the malocclusion of the patient's orthodontic condition basedon visual display of the displayed images that represent thecorresponding orthodontic condition.

Moreover, while two image segments 4920, 4930 are shown and describedabove in conjunction with FIG. 49, within the scope of the presentinvention, additional or fewer image segments corresponding to more orfewer selected teeth may be visually provided on the user interface4900.

FIG. 50 is a flowchart illustrating real time dynamic orthodonticcondition representation in accordance with one embodiment of thepresent invention. Referring to FIGS. 48 and 50, at step 5010 anorthodontic arrangement including a plurality of image segments (forexample, the upper or lower teeth image arrangement) is displayed, forexample, on a user interface 4800 such as a computer terminal displayunit. Thereafter, when a selection of one or more movement indicatorcorresponding to an image segment is detected at step 5020, theorthodontic arrangement or positioning display on the user interface ismodified to reposition the image segment or tooth corresponding to theselected one or more movement indicators, for example, in the directionassociated with the selected movement indicator at step 5030.Thereafter, at step 5040, the modified display of the orthodonticarrangement is stored in a storage unit such as a memory.

In this manner, in one embodiment, users or doctors are provided with aconvenient tool to visually manipulate a virtual dentition model toattain the best or most accurate representation of the patient'sorthodontic conditions.

FIG. 51 is a flowchart illustrating dynamic orthodontic conditionvalidation in accordance with one embodiment of the present invention.Referring to FIGS. 49 and 51, at step 5110, an orthodontic arrangementincluding a plurality of image segments such as the upper teeth or lowerteeth arrangement is displayed on a user interface 4900. Thereafter atstep 5120, when a selection of an image segment in the displayedorthodontic arrangement is detected (for example, based on a userselection of a particular tooth in displayed on the user interface4900), an expanded image such as a thumbnail view of the selected imagesegment in the predetermined orthodontic condition is retrieved, forexample, from a storage unit such as a computer memory at step 5130.That is, in one embodiment, at step 5130, based on the predeterminedmalocclusion under consideration, a close up view of the selected toothwith the predetermined malocclusion is retrieved and thereafterdisplayed at step 5140 on the user interface 4900, for example, as imagedisplay segment 4920.

In this manner, in one embodiment, simple and convenient way in which tovalidate or confirm one or more orthodontic conditions of a patient maybe visually provided using a virtual dental model and associated one ormore close up views representing the patient's orthodontic conditions.

Accordingly, a computer-implemented method in accordance with oneembodiment includes displaying an orthodontic related image includingone or more image segments, selecting one or more movement indicatorsassociated with a corresponding one or more of the image segments, anddynamically displaying a modified orthodontic related image based on theselected one or more movement indicators.

In one aspect, each one of the one or more movement indicators arerespectively associated with a corresponding one of the one or moreimage segments, and further, where each one of the one or more movementindicators includes a plurality of directional objects. In oneembodiment, the directional objects may include directional arrows,icons, images or any other suitable object which represents or isassociated with a predetermined direction.

Moreover, in a further aspect, each of the plurality of directionalobjects may correspond to a repositioned display of the correspondingone of the one or more image segments substantially in the direction ofthe corresponding each of the plurality of directional objects.

In yet another aspect, dynamically displaying the modified orthodonticrelated image may further include substantially real time display of themodified orthodontic related image in response to the selection of theone or more movement indicators.

Moreover, the computer implemented method may also include confirmingthe dynamically displayed modified orthodontic related imagecorresponding to one or more orthodontic conditions of a patient, whereconfirming the dynamically displayed modified orthodontic related imagemay include, in one aspect, classifying one or more malocclusions of thepatient.

Additionally, the one or more orthodontic conditions of the patient maybe associated with one or more of the sagittal, vertical, horizontal,arch length dentition, dentition rotation or dentition angulationcategory.

The orthodontic related image may be associated with one of a final oran ideal dental position, and in still another aspect, the modifiedorthodontic related image may be associated with an initial orthodonticcondition of a patient.

An apparatus in accordance with another embodiment includes an inputdevice, and a display unit operatively coupled to the input device, thedisplay unit configured to display an orthodontic related imageincluding one or more image segments, and dynamically display a modifiedorthodontic related image based on a selected one or more movementindicators displayed on the display unit based on an input signal fromthe input device.

The display unit may be further configured to dynamically display themodified orthodontic related image substantially in real time based onthe input device selection of the one or more movement indicators.

Further, the display unit may be further configured to display aconfirmation of the dynamically displayed modified orthodontic relatedimage corresponding to one or more orthodontic conditions of a patientbased on the input signal from the input device, and where the displayedconfirmation may include one or more classification of one or moremalocclusions of the patient.

In one aspect, the determination of the one or more classification ofthe one or more malocclusions is based on a lookup table. That is, asdiscussed above, in one embodiment, based upon the number of times theone or more movement indicators is selected, a correspondingmalocclusion classification for the associated tooth may be retrievedfrom a database.

A computer-implemented method in still another embodiment of the presentinvention includes displaying a first orthodontic related image at apredetermined location in a display unit, the orthodontic related imageincluding one or more image segments, selecting one of the one or moreimage segments, and displaying a second orthodontic related imageassociated with a predetermined orthodontic condition for the selectedone of the one or more image segments.

The method may also include retrieving the second orthodontic relatedimage based on the selected one of the one or more image segments.

Additionally, the method may also include generating the secondorthodontic related image associated with the predetermined orthodonticcondition for the selected one of the one or more image segments.

In still another aspect, the method may include confirming the displayedsecond orthodontic related image for the selected one of the one or moreimage segments corresponding to an initial orthodontic condition of apatient.

The predetermined orthodontic condition may include one of crossbite,underbite, overbite, overjet, spacing or crowding, arch shape, incisorprofile, inclination of posterior of upper or lower arch, bicuspid orcuspid rotation, missing tooth, and midline discrepancy.

Further, the method may include storing the second orthodontic relatedimage associated with the selected one of the one or more imagesegments.

In yet still another aspect, the second orthodontic related image mayinclude an expanded image of the predetermined orthodontic condition forthe selected one of the one or more image segments, where the expandedimage may include a thumbnail image.

Moreover, the selected one of the one or more image segments in yetanother embodiment may include a tooth image.

Also, the expanded image may display the tooth image associated with thepredetermined orthodontic condition in relative spatial relationshipwith one or more teeth images in close proximity to the tooth image.

An apparatus in accordance with still another embodiment includes aninput device, and a display unit operatively coupled to the inputdevice, the display unit configured to display a first orthodonticrelated image at a predetermined location, the orthodontic related imageincluding one or more image segments, and to display a secondorthodontic related image associated with a predetermined orthodonticcondition based on an input signal from the input device associated withthe selection of one of the one or more image segments.

The display unit may be configured to retrieve the second orthodonticrelated image based on the selected one of the one or more imagesegments.

Also, the display unit may be configured to the second orthodonticrelated image associated with the predetermined orthodontic conditionfor the selected one of the one or more image segments.

The input device may be configured to provide a signal associated with aconfirmation of the displayed second orthodontic related image for theselected one of the one or more image segments corresponding to aninitial orthodontic condition of a patient.

The predetermined orthodontic condition may include one of crossbite,underbite, overbite, overjet, spacing or crowding, arch shape, incisorprofile, inclination of posterior of upper or lower arch, bicuspid orcuspid rotation, missing tooth, and midline discrepancy.

In another aspect, the apparatus may also include a storage unitoperatively coupled to the display unit for storing the secondorthodontic related image associated with the selected one of the one ormore image segments.

Additionally, the second orthodontic related image may include anexpanded image of the predetermined orthodontic condition for theselected one of the one or more image segments.

Also, the display unit may be further configured to display the expandedimage to display the tooth image associated with the predeterminedorthodontic condition in relative spatial relationship with one or moreteeth images in close proximity to the tooth image.

Various other modifications and alterations in the structure and methodof operation of this invention will be apparent to those skilled in theart without departing from the scope and spirit of the invention.Although the invention has been described in connection with specificpreferred embodiments, it should be understood that the invention asclaimed should not be unduly limited to such specific embodiments. It isintended that the following claims define the scope of the presentinvention and that structures and methods within the scope of theseclaims and their equivalents be covered thereby.

1. A computer-implemented method, comprising: displaying an orthodonticrelated image including one or more image segments; selecting one ormore movement indicators associated with a corresponding one or more ofthe image segments; and dynamically displaying a modified orthodonticrelated image based on the selected one or more movement indicators. 2.The method of claim 1 wherein each one of the one or more movementindicators are respectively associated with a corresponding one of theone or more image segments.
 3. The method of claim 2 wherein each one ofthe one or more movement indicators includes a plurality of directionalobjects.
 4. The method of claim 3 wherein each of the plurality ofdirectional objects correspond to a repositioned display of thecorresponding one of the one or more image segments substantially in thedirection of the corresponding each of the plurality of directionalobjects.
 5. The method of claim 1 wherein dynamically displaying themodified orthodontic related image further includes substantially realtime display of the modified orthodontic related image in response tothe selection of the one or more movement indicators.
 6. The method ofclaim 1 further including confirming the dynamically displayed modifiedorthodontic related image corresponding to one or more orthodonticconditions of a patient.
 7. The method of claim 6 wherein confirming thedynamically displayed modified orthodontic related image includesclassifying one or more malocclusions of the patient.
 8. The method ofclaim 6 wherein the one or more orthodontic conditions of the patient isassociated with one or more of the sagittal, vertical, horizontal, archlength dentition, dentition rotation or dentition angulation category.9. The method of claim 1 wherein the orthodontic related image isassociated with one of a final or an ideal dental position.
 10. Themethod of claim 1 wherein the modified orthodontic related image isassociated with an initial orthodontic condition of a patient.
 11. Themethod of claim 1 wherein the one or more movement indicators includesone or more directional objects.
 12. An apparatus, comprising: an inputdevice; and a display unit operatively coupled to the input device, thedisplay unit configured to display an orthodontic related imageincluding one or more image segments, and dynamically display a modifiedorthodontic related image based on a selected one or more movementindicators displayed on the display unit based on an input signal fromthe input device.
 13. The apparatus of claim 12 wherein each one of theone or more movement indicators are respectively associated with acorresponding one of the one or more image segments.
 14. The apparatusof claim 13 wherein each one of the one or more movement indicatorsincludes a plurality of directional objects.
 15. The apparatus of claim14 wherein each of the plurality of directional objects correspond to arepositioned display of the corresponding one of the one or more imagesegments substantially in the direction of the corresponding each of theplurality of directional objects.
 16. The apparatus of claim 12 whereinthe display unit is further configured to dynamically display themodified orthodontic related image substantially in real time based onthe input device selection of the one or more movement indicators. 17.The apparatus of claim 12 wherein the display unit is further configuredto display a confirmation of the dynamically displayed modifiedorthodontic related image corresponding to one or more orthodonticconditions of a patient based on the input signal from the input device.18. The apparatus of claim 17 wherein the displayed confirmationincludes one or more classification of one or more malocclusions of thepatient.
 19. The apparatus of claim 18 wherein the determination of theone or more classification of the one or more malocclusions is based ona lookup table.
 20. The apparatus of claim 17 wherein the one or moreorthodontic conditions of the patient is associated with one or more ofthe sagittal, vertical, horizontal, arch length dentition, dentitionrotation or dentition angulation category.
 21. The apparatus of claim 12wherein the orthodontic related image is associated with one of a finalor an ideal dental position.
 22. The apparatus of claim 12 wherein themodified orthodontic related image is associated with an initialorthodontic condition of a patient.
 23. The apparatus of claim 12wherein the one or more movement indicators includes one or moredirectional objects.
 24. A computer-implemented method, comprising:displaying a first orthodontic related image at a predetermined locationin a display unit, the orthodontic related image including one or moreimage segments; selecting one of the one or more image segments; anddisplaying a second orthodontic related image associated with apredetermined orthodontic condition for the selected one of the one ormore image segments.
 25. The method of claim 24 further includingretrieving the second orthodontic related image based on the selectedone of the one or more image segments.
 26. The method of claim 24further including generating the second orthodontic related imageassociated with the predetermined orthodontic condition for the selectedone of the one or more image segments.
 27. The method of claim 24further including confirming the displayed second orthodontic relatedimage for the selected one of the one or more image segmentscorresponding to an initial orthodontic condition of a patient.
 28. Themethod of claim 24 wherein the predetermined orthodontic conditionincludes one of crossbite, underbite, overbite, overjet, spacing orcrowding, arch shape, incisor profile, inclination of posterior of upperor lower arch, bicuspid or cuspid rotation, missing tooth, and midlinediscrepancy.
 29. The method of claim 24 further including storing thesecond orthodontic related image associated with the selected one of theone or more image segments.
 30. The method of claim 24 wherein thesecond orthodontic related image includes an expanded image of thepredetermined orthodontic condition for the selected one of the one ormore image segments.
 31. The method of claim 30 wherein the expandedimage includes a thumbnail image.
 32. The method of claim 30 wherein theselected one of the one or more image segments includes a tooth image.33. The method of claim 32 wherein the expanded image displays the toothimage associated with the predetermined orthodontic condition inrelative spatial relationship with one or more teeth images in closeproximity to the tooth image.
 34. An apparatus, comprising: an inputdevice; and a display unit operatively coupled to the input device, thedisplay unit configured to display a first orthodontic related image ata predetermined location, the orthodontic related image including one ormore image segments, and to display a second orthodontic related imageassociated with a predetermined orthodontic condition based on an inputsignal from the input device associated with the selection of one of theone or more image segments.
 35. The apparatus of claim 34 wherein thedisplay unit is further configured to retrieve the second orthodonticrelated image based on the selected one of the one or more imagesegments.
 36. The apparatus of claim 34 wherein the display unit isfurther configured to the second orthodontic related image associatedwith the predetermined orthodontic condition for the selected one of theone or more image segments.
 37. The apparatus of claim 34 wherein theinput device is configured to provide a signal associated with aconfirmation of the displayed second orthodontic related image for theselected one of the one or more image segments corresponding to aninitial orthodontic condition of a patient.
 38. The apparatus of claim34 wherein the predetermined orthodontic condition includes one ofcrossbite, underbite, overbite, overjet, spacing or crowding, archshape, incisor profile, inclination of posterior of upper or lower arch,bicuspid or cuspid rotation, missing tooth, and midline discrepancy. 39.The apparatus of claim 34 further including a storage unit operativelycoupled to the display unit for storing the second orthodontic relatedimage associated with the selected one of the one or more imagesegments.
 40. The apparatus of claim 34 wherein the second orthodonticrelated image includes an expanded image of the predeterminedorthodontic condition for the selected one of the one or more imagesegments.
 41. The apparatus of claim 40 wherein the expanded imageincludes a thumbnail image.
 42. The apparatus of claim 40 wherein theselected one of the one or more image segments includes a tooth image.43. The apparatus of claim 42 wherein the display unit is furtherconfigured to display the expanded image to display the tooth imageassociated with the predetermined orthodontic condition in relativespatial relationship with one or more teeth images in close proximity tothe tooth image.